PASSML: combining evolutionary inference and protein secondary structure prediction. - Pietro Liò; N. Goldman; Jeffrey L. Thorne; David T. Jones (Bioinform., 1998)

Finding pathogenicity islands and gene transfer events in genome data. - Pietro Liò; Marina Vannucci (Bioinform., 2000)

Wavelet change-point prediction of transmembrane proteins. - Pietro Liò; Marina Vannucci (Bioinform., 2000)

Dimensionality and Dependence Problems in Statistical Genomics. - Pietro Liò (Briefings Bioinform., 2003)

Wavelets in bioinformatics and computational biology: state of art and perspectives. - Pietro Liò (Bioinform., 2003)

Identification of DNA regulatory motifs using Bayesian variable selection. - Mahlet G. Tadesse; Marina Vannucci; Pietro Liò (Bioinform., 2004)

Keyword Searching in Hypercubic Manifolds. - Yu-En Lu; Steven Hand 001; Pietro Liò (Peer-to-Peer Computing, 2005)

The Influence of Risk Perception in Epidemics: A Cellular Agent Model. - Luca Sguanci; Pietro Liò; Franco Bagnoli (ACRI, 2006)

Modeling Evolutionary Dynamics of HIV Infection. - Luca Sguanci; Pietro Liò; Franco Bagnoli (CMSB, 2006)

Keyword Searching in Structured Overlays Via Content Distance Addressing. - Yu-En Lu; Steven Hand 001; Pietro Liò (DBISP2P, 2006)

A novel algorithm and web-based tool for comparing two alternative phylogenetic trees. - Tom M. W. Nye; Pietro Liò; Walter R. Gilks (Bioinform., 2006)

Human Heuristics for Autonomous Agents. - Franco Bagnoli; Andrea Guazzini; Pietro Liò (BIOWIRE, 2007)

Bio-Inspired Multi-agent Collaboration for Urban Monitoring Applications. - Uichin Lee; Eugenio Magistretti; Mario Gerla; Paolo Bellavista; Pietro Liò; Kang-Won Lee (BIOWIRE, 2007)

Wavelet-Domain Statistics of Packet Switching Networks Near Traffic Congestion. - Pietro Liò; Anna T. Lawniczak; Shengkun Xie; Jiaying Xu (BIOWIRE, 2007)

Beta Random Projection. - Yu-En Lu; Pietro Liò; Steven Hand 001 (BIOWIRE, 2007)

Identifying Regulatory Sites Using Neighborhood Species. - Claudia Angelini; Luisa Cutillo; Italia De Feis; Richard Carl Van der Wath; Pietro Liò (EvoBIO, 2007)

Forensic DNA and bioinformatics. - Lucia Bianchi; Pietro Liò (Briefings Bioinform., 2007)

MotifScorer: using a compendium of microarrays to identify regulatory motifs. - Matteo Brilli; Renato Fani; Pietro Liò (Bioinform., 2007)

Bottleneck Genes and Community Structure in the Cell Cycle Network of S. pombe. - Cécile Caretta-Cartozo; Paolo De Los Rios; Francesco Piazza; Pietro Liò (PLoS Comput. Biol., 2007)

Contact Network Modeling of Flu Epidemics. - Ian X. Y. Leung; Gareth Gibbs; Franco Bagnoli; Anil Sorathiya; Pietro Liò (ACRI, 2008)

A Stochastic Multi-agent Model of Stem Cell Proliferation. - Richard Carl Van der Wath; Pietro Liò (ACRI, 2008)

A Novel Mobility Model from a Heterogeneous Military MANET Trace. - Xiaofeng Lu; Yung-Chih Chen; Ian X. Y. Leung; Zhang Xiong 001; Pietro Liò (ADHOC-NOW, 2008)

Topological Metrics in Blast Data Mining: Plasmid and Nitrogen-Fixing Proteins Case Studies. - Pietro Liò; Matteo Brilli; Renato Fani (BIRD, 2008)

Combining Molecular and Physiological Data of Complex Disorders. - Emanuel Schwarz; F. Markus Leweke; Sabine Bahn; Pietro Liò (BIRD, 2008)

Bayesian Phylogeny on Grid. - Richard Carl Van der Wath; Elizabeth van der Wath; Antonio Carapelli; Francesco Nardi; Francesco Frati; Luciano Milanesi; Pietro Liò (BIRD, 2008)

Searching for Glycomics Role in Stem Cell Development. - Anil Sorathiya; Tadas Jucikas; Stephanie Piecewicz; Shiladitya Sengupta; Pietro Liò (CIBB, 2008)

On low dimensional random projections and similarity search. - Yu-En Lu; Pietro Liò; Steven Hand 001 (CIKM, 2008)

A Stochastic Single Cell Based Model of BrdU Measured Hematopoietic Stem Cell Kinetics. - Richard Carl Van der Wath; Pietro Liò (CMSB, 2008)

Identity Privacy Protection by Delayed Transmission in Pocket Switched Networks. - Xiaofeng Lu; Pan Hui 001; Pietro Liò; Zhang Xiong 001 (EUC (2), 2008)

Inference on Missing Values in Genetic Networks Using High-Throughput Data. - Zdena Koukolíková-Nicola; Pietro Liò; Franco Bagnoli (EvoBIO, 2008)

Bayesian Inference on Hidden Knowledge in High-Throughput Molecular Biology Data. - Viet Anh Nguyen; Zdena Koukolíková-Nicola; Franco Bagnoli; Pietro Liò (PRICAI, 2008)

Social Networking for Pervasive Adaptation. - Stuart M. Allen; Marco Conti; Jon Crowcroft; Robin Dunbar; Pietro Liò; José Fernando Ferreira Mendes; Refik Molva; Andrea Passarella; Ioannis Stavrakakis; Roger M. Whitaker (SASO Workshops, 2008)

Forensic genomics: kin privacy, driftnets and other open questions. - Frank Stajano; Lucia Bianchi; Pietro Liò; Douwe Korff (WPES, 2008)

Current trends in the bioinformatic sequence analysis of metabolic pathways in prokaryotes. - Matteo Brilli; Renato Fani; Pietro Liò (Briefings Bioinform., 2008)

Analysis of plasmid genes by phylogenetic profiling and visualization of homology relationships using Blast2Network. - Matteo Brilli; Alessio Mengoni; Marco Fondi; Marco Bazzicalupo; Pietro Liò; Renato Fani (BMC Bioinform., 2008)

Prediction by Graph Theoretic Measures of Structural Effects in Proteins Arising from Non-Synonymous Single Nucleotide Polymorphisms. - Tammy M. K. Cheng; Yu-En Lu; Michele Vendruscolo; Pietro Liò; Tom L. Blundell (PLoS Comput. Biol., 2008)

Combining Replicates and Nearby Species Data: A Bayesian Approach. - Claudia Angelini; Italia De Feis; Viet Anh Nguyen; Richard Carl Van der Wath; Pietro Liò (CIBB, 2009)

Fast centrality approximation in modular networks. - Shu Yan Chan; Ian X. Y. Leung; Pietro Liò (CIKM-CNIKM, 2009)

On optimising personal network size to manage information flow. - Yu-En Lu; Sam G. B. Roberts; Tammy M. K. Cheng; Robin Dunbar; Pietro Liò; Jon Crowcroft (CIKM-CNIKM, 2009)

Formal Analysis of the Genetic Toggle. - Giampaolo Bella; Pietro Liò (CMSB, 2009)

Size Matters: Variation in Personal Network Size, Personality and Effect on Information Transmission. - Yu-En Lu; Sam G. B. Roberts; Pietro Liò; Robin Dunbar; Jon Crowcroft (CSE (4), 2009)

Information Processing and Timing Mechanisms in Vision. - Andrea Guazzini; Pietro Liò; Andrea Passarella; Marco Conti (ICANN (1), 2009)

A Case Study of ICA with Multi-scale PCA of Simulated Traffic Data. - Shengkun Xie; Pietro Liò; Anna T. Lawniczak (ICANN (2), 2009)

Mathematical Model of HIV Superinfection and Comparative Drug Therapy. - Anil Sorathiya; Pietro Liò; Luca Sguanci (ICARIS, 2009)

Using Mutual Information and Models of Evolution for Improved Pattern Petection. - Stephan Kitchovitch; Ian X. Y. Leung; Yuedong Song; Pietro Liò (IJCBS, 2009)

Identification of structurally important amino acids in proteins by graph-theoretic measures. - Tammy M. K. Cheng; Yu-En Lu; Pietro Liò (KDD Workshop on Statistical and Relational Learning in Bioinformatics, 2009)

Substitution Matrices and Mutual Information Approaches to Modeling Evolution. - Stephan Kitchovitch; Yuedong Song; Richard Carl Van der Wath; Pietro Liò (LION, 2009)

Bio-inspired multi-agent data harvesting in a proactive urban monitoring environment. - Uichin Lee; Eugenio Magistretti; Mario Gerla; Paolo Bellavista; Pietro Liò; Kang-Won Lee (Ad Hoc Networks, 2009)

Trends in modeling Biomedical Complex Systems. - Luciano Milanesi; Paolo Romano 001; Gastone C. Castellani; Daniel Remondini; Pietro Liò (BMC Bioinform., 2009)

Clinical bioinformatics for complex disorders: a schizophrenia case study. - Emanuel Schwarz; F. Markus Leweke; Sabine Bahn; Pietro Liò (BMC Bioinform., 2009)

Minimizing Detection Probability Routing in Ad Hoc Networks Using Directional Antennas. - Xiaofeng Lu; Don Towsley; Pietro Liò; Fletcher Wicker; Zhang Xiong 001 (EURASIP J. Wirel. Commun. Netw., 2009)

Analysis and Optimization of C3 Photosynthetic Carbon Metabolism. - Giovanni Stracquadanio; Renato Umeton; Alessio Papini; Pietro Liò; Giuseppe Nicosia (BIBE, 2010)

A New Approach for Epileptic Seizure Detection using Extreme Learning Machine. - Yuedong Song; Sarita Azad; Pietro Liò (BIOSIGNALS, 2010)

Generic spaced DNA motif discovery using Genetic Algorithm. - Tak-Ming Chan; Kwong-Sak Leung; Kin-Hong Lee; Pietro Liò (IEEE Congress on Evolutionary Computation, 2010)

StochKit-FF: Efficient Systems Biology on Multicore Architectures. - Marco Aldinucci; Andrea Bracciali; Pietro Liò; Anil Sorathiya; Massimo Torquati (Euro-Par Workshops, 2010)

Formal reasoning on qualitative models of coinfection of HIV and Tuberculosis and HAART therapy. - Anil Sorathiya; Andrea Bracciali; Pietro Liò (BMC Bioinform., 2010)

Formal Synthetic Immunology. - Marco Aldinucci; Andrea Bracciali; Pietro Liò (ERCIM News, 2010)

Biologically inspired networking [Guest Editorial]. - Pietro Liò; Dinesh C. Verma (IEEE Netw., 2010)

Cognitive network dynamics in chatlines. - Andrea Guazzini; Pietro Liò; Franco Bagnoli; Andrea Passarella; Marco Conti (ICCS, 2010)

Risk perception and disease spread on social networks. - Stephan Kitchovitch; Pietro Liò (ICCS, 2010)

Statistical mechanics of rumour spreading in network communities. - Massimo Ostilli; Eiko Yoneki; Ian X. Y. Leung; José F. F. Mendes; Pietro Liò; Jon Crowcroft (ICCS, 2010)

An integrated modelling approach for R5-X4 mutation and HAART therapy assessment. - Anil Sorathiya; Andrea Bracciali; Pietro Liò (Swarm Intell., 2010)

Detection Probability Estimation of Directional Antennas and Omni-Directional Antennas. - Xiaofeng Lu; Fletcher Wicker; Don Towsley; Zhang Xiong 001; Pietro Liò (Wirel. Pers. Commun., 2010)

Osteoporosis: a multiscale modeling viewpoint. - Nicola Paoletti; Pietro Liò; Emanuela Merelli; Marco Viceconti (CMSB, 2011)

Design of robust metabolic pathways. - Renato Umeton; Giovanni Stracquadanio; Anilkumar Sorathiya; Pietro Liò; Alessio Papini; Giuseppe Nicosia (DAC, 2011)

Unity in Diversity: Phylogenetic-inspired Techniques for Reverse Engineering and Detection of Malware Families. - Wei Ming Khoo; Pietro Lio' (SysSec@DIMVA, 2011)

Evolving Model of Opportunistic Routing in Delay Tolerant Networks. - Xiaofeng Lu; Pan Hui 001; Pietro Liò (MSN, 2011)

Parallel Hematopoietic Stem Cell Division Rate Estimation Using an Agent-Based Model on the Grid. - Richard Carl Van der Wath; Elizabeth van der Wath; Pietro Liò (PDP, 2011)

Message from the workshop on the future of social networking. - Eiko Yoneki; Jon Crowcroft; Pietro Liò; Neil Walton; Milan Vojnovic; Roger M. Whitaker (Comput. Commun. Rev., 2011)

Biological principles for future internet architecture design. - Sasitharan Balasubramaniam; Kenji Leibnitz; Pietro Liò; Dmitri Botvich; Masayuki Murata 001 (IEEE Commun. Mag., 2011)

Intra-City Urban Network and Traffic Flow Analysis from GPS Mobility Trace - Ian X. Y. Leung; Shu Yan Chan; Pan Hui 001; Pietro Liò (CoRR, 2011)

Multiple verification in computational modeling of bone pathologies - Pietro Liò; Emanuela Merelli; Nicola Paoletti (CompMod, 2011)

Information dynamics algorithm for detecting communities in networks - Emanuele Massaro; Andrea Guazzini; Franco Bagnoli; Pietro Liò (CoRR, 2011)

A Combined Process Algebraic and Stochastic Approach to Bone Remodeling. - Pietro Liò; Emanuela Merelli; Nicola Paoletti; Marco Viceconti (CS2Bio@DisCoTec, 2011)

Methodological Bridges for Multi-Level Systems. - Emanuela Merelli; Nicola Paoletti; Pietro Liò (FET, 2011)

Computing with Metabolic Machines. - Claudio Angione; Giovanni Carapezza; Jole Costanza; Pietro Liò; Giuseppe Nicosia (Turing-100, 2012)

Multi-objective Optimisation, Sensitivity and Robustness Analysis in FBA Modelling. - Jole Costanza; Giovanni Carapezza; Claudio Angione; Pietro Liò; Giuseppe Nicosia (CMSB, 2012)

Robust design of microbial strains. - Jole Costanza; Giovanni Carapezza; Claudio Angione; Pietro Liò; Giuseppe Nicosia (Bioinform., 2012)

Modelling osteomyelitis. - Pietro Liò; Nicola Paoletti; Mohammad Ali Moni; Kathryn Atwell; Emanuela Merelli; Marco Viceconti (BMC Bioinform., 2012)

An adaptive directional MAC protocol for ad hoc networks using directional antennas. - Xiaofeng Lu; Don Towsley; Pietro Liò; Zhang Xiong 001 (Sci. China Inf. Sci., 2012)

Disease processes as hybrid dynamical systems - Pietro Liò; Emanuela Merelli; Nicola Paoletti (HSB, 2012)

How to Compute with Metabolism in Bacteria? - Claudio Angione; Pietro Liò; Giuseppe Nicosia (ERCIM News, 2012)

Opportunistic routing through conjugation in bacteria communication nanonetwork. - Pietro Liò; Sasitharan Balasubramaniam (Nano Commun. Networks, 2012)

Multilevel Computational Modeling and Quantitative Analysis of Bone Remodeling. - Nicola Paoletti; Pietro Liò; Emanuela Merelli; Marco Viceconti (IEEE ACM Trans. Comput. Biol. Bioinform., 2012)

Multiple Verification in Complex Biological Systems: The Bone Remodelling Case Study. - Ezio Bartocci; Pietro Liò; Emanuela Merelli; Nicola Paoletti (Trans. Comp. Sys. Biology, 2012)

Methodologies for Systems Medicine: Time to Join the Forces of Bioengineering and Bioinformatics. - Pietro Liò (BIOSTEC, 2013)

Comparing Viral (HIV) and Bacterial (Staphylococcus aureus) Infection of the Bone Tissue. - Mohammad Ali Moni; Pietro Liò; Luciano Milanesi (BIOINFORMATICS, 2013)

Pareto epsilon-dominance and identifiable solutions for BioCAD modeling. - Claudio Angione; Jole Costanza; Giovanni Carapezza; Pietro Liò; Giuseppe Nicosia (DAC, 2013)

Multi objective design for bacterial communication networks. - Claudio Angione; Giovanni Carapezza; Jole Costanza; Pietro Liò; Giuseppe Nicosia (ICC Workshops, 2013)

Speeding up the transition to collective awareness. - Luce Jacovella; Pietro Liò (ICC Workshops, 2013)

It measures like me: An IoTs algorithm in WSNs based on heuristics behavior and clustering methods. - Alessandro Di Stefano; Aurelio La Corte; Marco Leotta; Pietro Liò; Marialisa Scatà (Ad Hoc Networks, 2013)

CytoHiC: a cytoscape plugin for visual comparison of Hi-C networks. - Yoli Shavit; Pietro Liò (Bioinform., 2013)

A Location Prediction Algorithm for Mobile Communications Using Directional Antennas. - Xiaofeng Lu; Pietro Liò; Ben Hui; Haifei Jin (Int. J. Distributed Sens. Networks, 2013)

Design and strain selection criteria for bacterial communication networks. - Claudio Angione; Giovanni Carapezza; Jole Costanza; Pietro Liò; Giuseppe Nicosia (Nano Commun. Networks, 2013)

A review of experimental opportunities for molecular communication. - Sasitharan Balasubramaniam; Sigal Ben-Yehuda; Sophie Pautot; Aldo Jesorka; Pietro Liò; Yevgeni Koucheryavy (Nano Commun. Networks, 2013)

Pareto Optimality in Organelle Energy Metabolism Analysis. - Claudio Angione; Giovanni Carapezza; Jole Costanza; Pietro Liò; Giuseppe Nicosia (IEEE ACM Trans. Comput. Biol. Bioinform., 2013)

Endovascular Mobile Sensor Network for Detecting Circulating Tumoral Cells. - Gianluca Reali; Mauro Femminella; Luca Felicetti; Pietro Liò (BODYNETS, 2014)

Drug Repurposing by Optimizing Mining of Genes Target Association. - Aicha Boutorh; Naruemon Pratanwanich; Ahmed Guessoum; Pietro Liò (CIBB, 2014)

Automated Detection of Fluorescent Probes in Molecular Imaging. - Fiona Kathryn Hamey; Yoli Shavit; Valdone Maciulyte; Christopher Town 001; Pietro Liò; Sabrina Tosi (CIBB, 2014)

Applications of Network-based Survival Analysis Methods for Pathways Detection in Cancer. - Antonella Iuliano; Annalisa Occhipinti; Claudia Angelini; Italia De Feis; Pietro Liò (CIBB, 2014)

Improving Literature-Based Discovery with Advanced Text Mining. - Anna Korhonen; Yufan Guo; Simon Baker; Meliha Yetisgen-Yildiz; Ulla Stenius; Masashi Narita; Pietro Liò (CIBB, 2014)

NuChart-II: A Graph-Based Approach for Analysis and Interpretation of Hi-C Data. - Fabio Tordini; Maurizio Drocco; Ivan Merelli; Luciano Milanesi; Pietro Liò; Marco Aldinucci (CIBB, 2014)

Computing Longevity: Insights from Controls. - Pietro Liò (FMMB, 2014)

Who Wrote This? Textual Modeling with Authorship Attribution in Big Data. - Naruemon Pratanwanich; Pietro Liò (ICDM Workshops, 2014)

The Bio-Inspired and Social Evolution of Node and Data in a Multilayer Network. - Marialisa Scatà; Alessandro Di Stefano; Evelina Giacchi; Aurelio La Corte; Pietro Liò (DCNET, 2014)

Nodes Density Adaptive Opportunistic Forwarding Protocol for Intermittently Connected Networks. - Xiaofeng Lu; Pietro Liò; Pan Hui 001; Zhaowei Qu (IIKI, 2014)

A Molecular Communication System in Blood Vessels for Tumor Detection. - Luca Felicetti; Mauro Femminella; Gianluca Reali; Pietro Liò (NANOCOM, 2014)

FisHiCal: an R package for iterative FISH-based calibration of Hi-C data. - Yoli Shavit; Fiona Kathryn Hamey; Pietro Liò (Bioinform., 2014)

Network-based analysis of comorbidities risk during an infection: SARS and HIV case studies. - Mohammad Ali Moni; Pietro Liò (BMC Bioinform., 2014)

Exploring the complexity of pathway-drug relationships using latent Dirichlet allocation. - Naruemon Pratanwanich; Pietro Liò (Comput. Biol. Chem., 2014)

comoR: a software for disease comorbidity risk assessment. - Mohammad Ali Moni; Pietro Liò (J. Clin. Bioinform., 2014)

Forward and Reverse coding for chromosome transfer in bacterial nanonetworks. - Vitaly Petrov; Sasitharan Balasubramaniam; Rahmi Lale; Dmitri Moltchanov; Pietro Liò; Yevgeni Koucheryavy (Nano Commun. Networks, 2014)

Directional communication with movement prediction in mobile wireless sensor networks. - Xiaofeng Lu; Zhaowei Qu; Pietro Liò; Pan Hui 001; Qi Li 002; Peng Lu; Rongfang Bie (Pers. Ubiquitous Comput., 2014)

Bioinformatics Challenges and Potentialities in Studying Extreme Environments. - Claudio Angione; Pietro Liò; Sandra Pucciarelli; Basarbatu Can; Maxwell Conway; Marina Lotti; Habib Bokhari; Alessio Mancini; Ugur Sezerman; Andrea Telatin (CIBB, 2015)

NuchaRt: Embedding High-Level Parallel Computing in R for Augmented Hi-C Data Analysis. - Fabio Tordini; Ivan Merelli; Pietro Liò; Luciano Milanesi; Marco Aldinucci (CIBB, 2015)

Privacy Information Security Classification and Comparison between the Westerner and Chinese. - Xiaofeng Lu; Pietro Liò (IIKI, 2015)

Multi omic oscillations in bacterial pathways. - Francesco Bardozzo; Pietro Liò; Roberto Tagliaferri (IJCNN, 2015)

Parallel Exploration of the Nuclear Chromosome Conformation with NuChart-II. - Fabio Tordini; Maurizio Drocco; Claudia Misale; Luciano Milanesi; Pietro Liò; Ivan Merelli; Marco Aldinucci (PDP, 2015)

Advances in Artificial Life: Synthesis and Simulation of Living Systems: Editorial. - Pietro Liò; Orazio Miglino; Giuseppe Nicosia; Stefano Nolfi; Mario Pavone (Artif. Life, 2015)

DAPPER: a data-mining resource for protein-protein interactions. - Syed Haider; Zoltan Lipinszki; Marcin Przewloka; Yaseen Ladak; Pier D'Avino; Yuu Kimata; Pietro Liò; David Glover (BioData Min., 2015)

MeDuSa: a multi-draft based scaffolder. - Emanuele Bosi; Beatrice Donati; Marco Galardini; Sara Brunetti; Marie-France Sagot; Pietro Liò; Pierluigi Crescenzi; Renato Fani; Marco Fondi (Bioinform., 2015)

CytoCom: a Cytoscape app to visualize, query and analyse disease comorbidity networks. - Mohammad Ali Moni; Haoming Xu; Pietro Liò (Bioinform., 2015)

Network regularised Cox regression and multiplex network models to predict disease comorbidities and survival of cancer. - Haoming Xu; Mohammad Ali Moni; Pietro Liò (Comput. Biol. Chem., 2015)

Comorbidity networks: beyond disease correlations. - Enrico Capobianco; Pietro Liò (J. Complex Networks, 2015)

The BioMart community portal: an innovative alternative to large, centralized data repositories. - Damian Smedley; Syed Haider; Steffen Durinck; Luca Pandini; Paolo Provero; James E. Allen; Olivier Arnaiz; Mohammad Hamza Awedh; Richard A. Baldock; Giulia Barbiera; Philippe Bardou; Tim Beck; et al. (Nucleic Acids Res., 2015)

Modelling Circulating Tumour Cells for Personalised Survival Prediction in Metastatic Breast Cancer. - Gianluca Ascolani; Annalisa Occhipinti; Pietro Liò (PLoS Comput. Biol., 2015)

Analysis and design of molecular machines. - Claudio Angione; Jole Costanza; Giovanni Carapezza; Pietro Liò; Giuseppe Nicosia (Theor. Comput. Sci., 2015)

Multilayer Data and Document Stratification for Comorbidity Analysis. - Kevin Heffernan; Pietro Liò; Simone Teufel (CIBB, 2016)

Channel modelling of molecular communications across blood vessels and nerves. - Peng He 001; Yuming Mao; Qiang Liu 016; Pietro Liò; Kun Yang 001 (ICC, 2016)

MolComML: The Molecular Communication Markup Language. - Eduard Alarcón; Raul Gomez Cid-Fuentes; Alan Davy; Luca Felicetti; Mauro Femminella; Pietro Liò; Gianluca Reali; Josep Solé-Pareta (NANOCOM, 2016)

Warped Matrix Factorisation for Multi-view Data Integration. - Naruemon Pratanwanich; Pietro Liò; Oliver Stegle (ECML/PKDD (2), 2016)

X-CNN: Cross-modal convolutional neural networks for sparse datasets. - Petar Velickovic; Duo Wang; Nicholas D. Lane; Pietro Liò (SSCI, 2016)

Systems medicine of inflammaging. - Gastone C. Castellani; Giulia Menichetti; Paolo Garagnani; Maria Giulia Bacalini; Chiara Pirazzini; Claudio Franceschi; Sebastiano Collino; Claudia Sala; Daniel Remondini; Enrico Giampieri; Ettore Mosca; Matteo Bersanelli; et al. (Briefings Bioinform., 2016)

How computer science can help in understanding the 3D genome architecture. - Yoli Shavit; Ivan Merelli; Luciano Milanesi; Pietro Liò (Briefings Bioinform., 2016)

Hierarchical block matrices as efficient representations of chromosome topologies and their application for 3C data integration. - Yoli Shavit; Barnabas James Walker; Pietro Liò (Bioinform., 2016)

Muxstep: an open-source C ++ multiplex HMM library for making inferences on multiple data types. - Petar Velickovic; Pietro Liò (Bioinform., 2016)

Multiplex methods provide effective integration of multi-omic data in genome-scale models. - Claudio Angione; Maxwell Conway; Pietro Liò (BMC Bioinform., 2016)

Animal inference on human mitochondrial diseases. - Francesco Nardi; Francesco Frati; Pietro Liò (Comput. Biol. Chem., 2016)

Molecular multiplex network inference using Gaussian mixture hidden Markov models. - Petar Velickovic; Pietro Liò (J. Complex Networks, 2016)

Fast Bayesian Non-Negative Matrix Factorisation and Tri-Factorisation. - Thomas Brouwer; Jes Frellsen; Pietro Liò (CoRR, 2016)

Applications of molecular communications to medicine: A survey. - Luca Felicetti; Mauro Femminella; Gianluca Reali; Pietro Liò (Nano Commun. Networks, 2016)

Computational Modeling, Formal Analysis, and Tools for Systems Biology. - Ezio Bartocci; Pietro Liò (PLoS Comput. Biol., 2016)

Distance-Based Opportunistic Mobile Data Offloading. - Xiaofeng Lu; Pietro Liò; Pan Hui 001 (Sensors, 2016)

Bayesian Hybrid Matrix Factorisation for Data Integration. - Thomas Brouwer; Pietro Liò (AISTATS, 2017)

Hierarchical Block Matrix Approach for Multi-view Clustering. - Angela Serra; Maria Domenica Guida; Pietro Lió; Roberto Tagliaferri (CIBB, 2017)

A big-data layered architecture for analyzing molecular communications systems in blood vessels. - Luca Felicetti; Mauro Femminella; Todor Ivanov; Pietro Liò; Gianluca Reali (NANOCOM, 2017)

Scientific Workflows on Clouds with Heterogeneous and Preemptible Instances. - Fabio Tordini; Marco Aldinucci; Paolo Viviani 001; Ivan Merelli; Pietro Liò (PARCO, 2017)

Comparative Study of Inference Methods for Bayesian Nonnegative Matrix Factorisation. - Thomas Brouwer; Jes Frellsen; Pietro Liò (ECML/PKDD (1), 2017)

A multiplex network approach for the analysis of intracranial pressure and heart rate data in traumatic brain injured patients. - Giovanna Maria Dimitri; Shruti Agrawal; Adam Young; Joseph Donnelly; Xiuyun Liu; Peter Smielewski; Peter Hutchinson; Marek Czosnyka; Pietro Liò; Christina Haubrich (Appl. Netw. Sci., 2017)

Opportunities for community awareness platforms in personal genomics and bioinformatics education. - Lucia Bianchi; Pietro Liò (Briefings Bioinform., 2017)

Making life difficult for Clostridium difficile: augmenting the pathogen's metabolic model with transcriptomic and codon usage data for better therapeutic target characterization. - Sara Saheb Kashaf; Claudio Angione; Pietro Liò (BMC Syst. Biol., 2017)

DrugClust: A machine learning approach for drugs side effects prediction. - Giovanna Maria Dimitri; Pietro Liò (Comput. Biol. Chem., 2017)

Learning Rare Word Representations using Semantic Bridging. - Victor Prokhorov; Mohammad Taher Pilehvar; Dimitri Kartsaklis; Pietro Liò; Nigel Collier (CoRR, 2017)

XFlow: 1D-2D Cross-modal Deep Neural Networks for Audiovisual Classification. - Catalina Cangea; Petar Velickovic; Pietro Liò (CoRR, 2017)

Cross-modal Recurrent Models for Human Weight Objective Prediction from Multimodal Time-series Data. - Petar Velickovic; Laurynas Karazija; Nicholas D. Lane; Sourav Bhattacharya; Edgar Liberis; Pietro Liò; Angela Chieh; Otmane Bellahsen; Matthieu Vegreville (CoRR, 2017)

Quantifying the Effects of Enforcing Disentanglement on Variational Autoencoders. - Momchil Peychev; Petar Velickovic; Pietro Liò (CoRR, 2017)

NuChart-II: The road to a fast and scalable tool for Hi-C data analysis. - Fabio Tordini; Maurizio Drocco; Claudia Misale; Luciano Milanesi; Pietro Liò; Ivan Merelli; Massimo Torquati; Marco Aldinucci (Int. J. High Perform. Comput. Appl., 2017)

Neural Models for Brain Networks Connectivity Analysis. - Razvan Kusztos; Giovanna Maria Dimitri; Pietro Lió (CIBB, 2018)

Multi-omic Network Regression: Methodology, Tool and Case Study. - Vandan Parmar; Pietro Lió (COMPLEX NETWORKS (2), 2018)

Investigating Diagrammatic Reasoning with Deep Neural Networks. - Duo Wang; Mateja Jamnik; Pietro Liò (Diagrams, 2018)

A Multi-modal Convolutional Neural Network Framework for the Prediction of Alzheimer's Disease. - Simeon E. Spasov; Luca Passamonti; Andrea Duggento; Pietro Liò; Nicola Toschi (EMBC, 2018)

High Performance Computing for Haplotyping: Models and Platforms. - Andrea Tangherloni; Leonardo Rundo; Simone Spolaor; Marco S. Nobile; Ivan Merelli; Daniela Besozzi; Giancarlo Mauri; Paolo Cazzaniga; Pietro Liò (Euro-Par Workshops, 2018)

Terminal Sensitive Data Protection by Adjusting Access Time Bidirectionally and Automatically. - Xiaofeng Lu; Chen Liang; Shengfei Zhang; Pietro Liò; Jing Sha (ICCCN, 2018)

Graph Attention Networks. - Petar Velickovic; Guillem Cucurull; Arantxa Casanova; Adriana Romero; Pietro Liò; Yoshua Bengio (ICLR (Poster), 2018)

Using deep data augmentation training to address software and hardware heterogeneities in wearable and smartphone sensing devices. - Akhil Mathur; Tianlin Zhang; Sourav Bhattacharya; Petar Velickovic; Leonid Joffe; Nicholas D. Lane; Fahim Kawsar; Pietro Liò (IPSN, 2018)

Automatic Inference of Cross-Modal Connection Topologies for X-CNNs. - Laurynas Karazija; Petar Velickovic; Pietro Liò (ISNN, 2018)

Neural network fusion: a novel CT-MR aortic aneurysm image segmentation method. - Duo Wang; Rui Zhang; Jin Zhu; Zhongzhao Teng; Yuan Huang 009; Filippo Spiga; Michael Hong-Fei Du; Jonathan H. Gillard; Qingsheng Lu; Pietro Liò (Image Processing, 2018)

A Logical Framework for Modelling Breast Cancer Progression. - Joëlle Despeyroux; Amy P. Felty; Pietro Liò; Carlos Olarte (MLCSB, 2018)

Cross-modal Recurrent Models for Weight Objective Prediction from Multimodal Time-series Data. - Petar Velickovic; Laurynas Karazija; Nicholas D. Lane; Sourav Bhattacharya; Edgar Liberis; Pietro Liò; Angela Chieh; Otmane Bellahsen; Matthieu Vegreville (PervasiveHealth, 2018)

Parallel swarm intelligence strategies for large-scale clustering based on MapReduce with application to epigenetics of aging. - Zakaria Benmounah; Souham Meshoul; Mohamed Batouche; Pietro Lio' (Appl. Soft Comput., 2018)

Seeing the wood for the trees: a forest of methods for optimization and omic-network integration in metabolic modelling. - Supreeta Vijayakumar; Maxwell Conway; Pietro Lió; Claudio Angione (Briefings Bioinform., 2018)

Parapred: antibody paratope prediction using convolutional and recurrent neural networks. - Edgar Liberis; Petar Velickovic; Pietro Sormanni; Michele Vendruscolo; Pietro Liò (Bioinform., 2018)

A study on multi-omic oscillations in Escherichia coli metabolic networks. - Francesco Bardozzo; Pietro Liò; Roberto Tagliaferri (BMC Bioinform., 2018)

STAble: a novel approach to de novo assembly of RNA-seq data and its application in a metabolic model network based metatranscriptomic workflow. - Igor Saggese; Elisa Bona; Maxwell Conway; Francesco Favero; Marco Ladetto; Pietro Liò; Giovanni Manzini; Flavio Mignone (BMC Bioinform., 2018)

Multi-omic analysis of signalling factors in inflammatory comorbidities. - Hui Xiao; Krzysztof Bartoszek; Pietro Lio' (BMC Bioinform., 2018)

Introducing Curvature to the Label Space. - Conor Sheehan; Ben Day; Pietro Liò (CoRR, 2018)

Towards Sparse Hierarchical Graph Classifiers. - Catalina Cangea; Petar Velickovic; Nikola Jovanovic 001; Thomas Kipf; Pietro Liò (CoRR, 2018)

Structure-Based Networks for Drug Validation. - Catalina Cangea; Arturas Grauslys; Pietro Liò; Francesco Falciani (CoRR, 2018)

Modelling trait dependent speciation with Approximate Bayesian Computation. - Krzysztof Bartoszek; Pietro Liò (CoRR, 2018)

Stochastic Channel Switching of Frequency-Encoded Signals in Molecular Communication Networks. - Peng He 001; Tadashi Nakano; Yuming Mao; Pietro Liò; Qiang Liu 016; Kun Yang 001 (IEEE Commun. Lett., 2018)

Guest Editors' Introduction to the Special Section on the 14th International Conference on Computational Methods in Systems Biology (CMSB 2016). - Ezio Bartocci; Pietro Liò; Nicola Paoletti (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

Computational Models for Trapping Ebola Virus Using Engineered Bacteria. - Daniel P. Martins; Michael Taynnan Barros; Massimiliano Pierobon; Meenakshisundaram Kandhavelu; Pietro Lio'; Sasitharan Balasubramaniam (IEEE ACM Trans. Comput. Biol. Bioinform., 2018)

Unseen Word Representation by Aligning Heterogeneous Lexical Semantic Spaces. - Victor Prokhorov; Mohammad Taher Pilehvar; Dimitri Kartsaklis; Pietro Liò; Nigel Collier (AAAI, 2019)

Dynamic Neural Network Channel Execution for Efficient Training. - Simeon E. Spasov; Pietro Liò (BMVC, 2019)

NeoHiC: A Web Application for the Analysis of Hi-C Data. - Daniele D'Agostino; Pietro Liò; Marco Aldinucci; Ivan Merelli (CIBB, 2019)

Improving QoE in Multi-layer Social Sensing: A Cognitive Architecture and Game Theoretic Model. - Alessandro Di Stefano; Marialisa Scatà; Aurelio La Corte; Sajal K. Das 001; Pietro Liò (SocialSens@CPSIoTWeek, 2019)

Deep Graph Infomax. - Petar Velickovic; William Fedus; William L. Hamilton; Pietro Liò; Yoshua Bengio; R. Devon Hjelm (ICLR (Poster), 2019)

A Machine Learning Tool for Interpreting Differences in Cognition Using Brain Features. - Tiago Azevedo; Luca Passamonti; Pietro Liò; Nicola Toschi (AIAI, 2019)

How Can We Make Gan Perform Better in Single Medical Image Super-Resolution? A Lesion Focused Multi-Scale Approach. - Jin Zhu; Guang Yang 006; Pietro Liò (ISBI, 2019)

Lesion focused super-resolution. - Jin Zhu; Guang Yang 006; Pietro Lió (Image Processing, 2019)

VideoNavQA: Bridging the Gap between Visual and Embodied Question Answering. - Catalina Cangea; Eugene Belilovsky; Pietro Liò; Aaron C. Courville (ViGIL@NeurIPS, 2019)

Machine Learning-Based Models for Early Stage Detection of Autism Spectrum Disorders. - Tania Akter; Md. Shahriare Satu; Md. Imran Khan; Mohammad Hanif Ali; Shahadat Uddin; Pietro Lió; Julian M. W. Quinn; Mohammad Ali Moni (IEEE Access, 2019)

GenHap: a novel computational method based on genetic algorithms for haplotype assembly. - Andrea Tangherloni; Simone Spolaor; Leonardo Rundo; Marco S. Nobile; Paolo Cazzaniga; Giancarlo Mauri; Pietro Liò; Ivan Merelli; Daniela Besozzi (BMC Bioinform., 2019)

Genetic effects of welding fumes on the development of respiratory system diseases. - Humayan Kabir Rana; Mst. Rashida Akhtar; M. Babul Islam; Mohammad Boshir Ahmed; Pietro Liò; Julian M. W. Quinn; Fazlul Huq; Mohammad Ali Moni (Comput. Biol. Medicine, 2019)

ASSCA: API sequence and statistics features combined architecture for malware detection. - Xiaofeng Lu; Fangshuo Jiang; Xiao Zhou; Shengwei Yi; Jing Sha; Pietro Liò (Comput. Networks, 2019)

ChronoMID - Cross-Modal Neural Networks for 3-D Temporal Medical Imaging Data. - Alexander G. Rakowski; Petar Velickovic; Enrico Dall'Ara; Pietro Liò (CoRR, 2019)

Unsupervised and interpretable scene discovery with Discrete-Attend-Infer-Repeat. - Duo Wang; Mateja Jamnik; Pietro Liò (CoRR, 2019)

Clique pooling for graph classification. - Enxhell Luzhnica; Ben Day; Pietro Liò (CoRR, 2019)

Spatio-Temporal Deep Graph Infomax. - Felix L. Opolka; Aaron Solomon; Catalina Cangea; Petar Velickovic; Pietro Liò; R. Devon Hjelm (CoRR, 2019)

Drug-Drug Adverse Effect Prediction with Graph Co-Attention. - Andreea Deac; Yu-Hsiang Huang; Petar Velickovic; Pietro Liò; Jian Tang 005 (CoRR, 2019)

On Graph Classification Networks, Datasets and Baselines. - Enxhell Luzhnica; Ben Day; Pietro Liò (CoRR, 2019)

ncRNA Classification with Graph Convolutional Networks. - Emanuele Rossi; Federico Monti; Michael M. Bronstein; Pietro Liò (CoRR, 2019)

Factorised Neural Relational Inference for Multi-Interaction Systems. - Ezra Webb; Ben Day; Helena Andrés-Terré; Pietro Lió (CoRR, 2019)

Perturbation theory approach to study the latent space degeneracy of Variational Autoencoders. - Helena Andrés-Terré; Pietro Lió (CoRR, 2019)

Towards Probabilistic Generative Models Harnessing Graph Neural Networks for Disease-Gene Prediction. - Vikash Singh; Pietro Liò (CoRR, 2019)

Co-Attentive Cross-Modal Deep Learning for Medical Evidence Synthesis and Decision Making. - Devin Taylor; Simeon E. Spasov; Pietro Liò (CoRR, 2019)

Dynamic survival prediction in intensive care units from heterogeneous time series without the need for variable selection or pre-processing. - Jacob Deasy; Pietro Liò; Ari Ercole (CoRR, 2019)

Impact of novel aggregation methods for flexible, time-sensitive EHR prediction without variable selection or cleaning. - Jacob Deasy; Ari Ercole; Pietro Liò (CoRR, 2019)

Decoupling feature propagation from the design of graph auto-encoders. - Paul Scherer; Helena Andrés-Terré; Pietro Liò; Mateja Jamnik (CoRR, 2019)

Personalisable Clinical Decision Support System. - Tamara Müller; Pietro Lió (ERCIM News, 2019)

Predicting factors for survival of breast cancer patients using machine learning techniques. - Mogana Darshini Ganggayah; Nur Aishah Taib; Yip Cheng Har; Pietro Lió; Sarinder Kaur Dhillon (BMC Medical Informatics Decis. Mak., 2019)

A parameter-efficient deep learning approach to predict conversion from mild cognitive impairment to Alzheimer's disease. - Simeon E. Spasov; Luca Passamonti; Andrea Duggento; Pietro Liò; Nicola Toschi (NeuroImage, 2019)

Social dynamics modeling of chrono-nutrition. - Alessandro Di Stefano; Marialisa Scatà; Supreeta Vijayakumar; Claudio Angione; Aurelio La Corte; Pietro Liò (PLoS Comput. Biol., 2019)

Proximal Distilled Evolutionary Reinforcement Learning. - Cristian Bodnar; Ben Day; Pietro Lió (AAAI, 2020)

Now You See Me (CME): Concept-based Model Extraction. - Dmitry Kazhdan; Botty Dimanov; Mateja Jamnik; Pietro Liò; Adrian Weller (CIKM (Workshops), 2020)

A deep spatiotemporal graph learning architecture for brain connectivity analysis. - Tiago Azevedo; Luca Passamonti; Pietro Liò; Nicola Toschi (EMBC, 2020)

Unsupervised stratification in neuroimaging through deep latent embeddings. - Giovanna Maria Dimitri; Simeon E. Spasov; Andrea Duggento; Luca Passamonti; Pietro Lio'; Nicola Toschi (EMBC, 2020)

A novel Graph Attention Network Architecture for modeling multimodal brain connectivity. - Alexandru-Catalin Filip; Tiago Azevedo; Luca Passamonti; Nicola Toschi; Pietro Liò (EMBC, 2020)

Resolution of Blockchain Conflicts through Heuristics-based Game Theory and Multilayer Network Modeling. - Alessandro Di Stefano; Damiano Di Francesco Maesa; Sajal K. Das 001; Pietro Liò (ICDCN, 2020)

Abstract Diagrammatic Reasoning with Multiplex Graph Networks. - Duo Wang; Mateja Jamnik; Pietro Liò (ICLR, 2020)

Arbitrary Scale Super-Resolution for Brain MRI Images. - Chuan Tan; Jin Zhu; Pietro Lio' (AIAI (1), 2020)

MARLeME: A Multi-Agent Reinforcement Learning Model Extraction Library. - Dmitry Kazhdan; Zohreh Shams; Pietro Liò (IJCNN, 2020)

Principal Neighbourhood Aggregation for Graph Nets. - Gabriele Corso; Luca Cavalleri; Dominique Beaini; Pietro Liò; Petar Velickovic (NeurIPS, 2020)

Constraining Variational Inference with Geometric Jensen-Shannon Divergence. - Jacob Deasy; Nikola Simidjievski; Pietro Lió (NeurIPS, 2020)

Path Integral Based Convolution and Pooling for Graph Neural Networks. - Zheng Ma; Junyu Xuan; Yu Guang Wang 001; Ming Li 065; Pietro Liò (NeurIPS, 2020)

On Second Order Behaviour in Augmented Neural ODEs. - Alexander Norcliffe; Cristian Bodnar; Ben Day; Nikola Simidjievski; Pietro Lió (NeurIPS, 2020)

Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks**To appear in the Proceedings of 2020 IEEE International Conference on Smart Computing (SMARTCOMP 2020). - Gevorg Yeghikyan; Felix L. Opolka; Mirco Nanni; Bruno Lepri; Pietro Liò (SMARTCOMP, 2020)

Privacy-Preserving Asynchronous Federated Learning Mechanism for Edge Network Computing. - Xiaofeng Lu; Yuying Liao; Pietro Liò; Pan Hui 001 (IEEE Access, 2020)

Domain-Oriented Topic Discovery Based on Features Extraction and Topic Clustering. - Xiaofeng Lu; Xiao Zhou; Wenting Wang; Pietro Liò; Pan Hui 001 (IEEE Access, 2020)

Bioinformatics methodologies for coeliac disease and its comorbidities. - Eugenio Del Prete; Angelo M. Facchiano; Pietro Liò (Briefings Bioinform., 2020)

Continuous authentication by free-text keystroke based on CNN and RNN. - Xiaofeng Lu; Shengfei Zhang; Pan Hui 001; Pietro Liò (Comput. Secur., 2020)

Latest advances in parallel, distributed, and network-based processing. - Ivan Merelli; Pietro Liò; Igor V. Kotenko; Daniele D'Agostino (Concurr. Comput. Pract. Exp., 2020)

A machine learning approach to investigate regulatory control circuits in bacterial metabolic pathways. - Francesco Bardozzo; Pietro Liò; Roberto Tagliaferri (CoRR, 2020)

Graph Convolutional Gaussian Processes For Link Prediction. - Felix L. Opolka; Pietro Liò (CoRR, 2020)

Adaptive Prediction Timing for Electronic Health Records. - Jacob Deasy; Ari Ercole; Pietro Liò (CoRR, 2020)

Towards a predictive spatio-temporal representation of brain data. - Tiago Azevedo; Luca Passamonti; Pietro Liò; Nicola Toschi (CoRR, 2020)

Learning distributed representations of graphs with Geo2DR. - Paul Scherer; Pietro Liò (CoRR, 2020)

Probabilistic Dual Network Architecture Search on Graphs. - Yiren Zhao; Duo Wang; Xitong Gao; Robert D. Mullins; Pietro Liò; Mateja Jamnik (CoRR, 2020)

ML-SIM: A deep neural network for reconstruction of structured illumination microscopy images. - Charles N. Christensen; Edward N. Ward; Pietro Lió; Clemens F. Kaminski (CoRR, 2020)

Learning Mobility Flows from Urban Features with Spatial Interaction Models and Neural Networks. - Gevorg Yeghikyan; Felix L. Opolka; Mirco Nanni; Bruno Lepri; Pietro Lio' (CoRR, 2020)

Neural Bipartite Matching. - Dobrik Georgiev; Pietro Lió (CoRR, 2020)

Kolmogorov Regularization for Link Prediction. - Paris D. L. Flood; Ramón Viñas 001; Pietro Liò (CoRR, 2020)

tvGP-VAE: Tensor-variate Gaussian Process Prior Variational Autoencoder. - Alex Campbell; Pietro Liò (CoRR, 2020)

The Computational Patient has Diabetes and a COVID. - Pietro Barbiero; Pietro Lió (CoRR, 2020)

Generalisable Relational Reasoning With Comparators in Low-Dimensional Manifolds. - Duo Wang; Mateja Jamnik; Pietro Liò (CoRR, 2020)

A Multiscale Graph Convolutional Network Using Hierarchical Clustering. - Alex Lipov; Pietro Liò (CoRR, 2020)

Uncertainty in Neural Relational Inference Trajectory Reconstruction. - Vasileios Karavias; Ben Day; Pietro Liò (CoRR, 2020)

Predicting Length of Stay in the Intensive Care Unit with Temporal Pointwise Convolutional Networks. - Emma Rocheteau; Pietro Liò; Stephanie L. Hyland (CoRR, 2020)

RicciNets: Curvature-guided Pruning of High-performance Neural Networks Using Ricci Flow. - Samuel Glass; Simeon E. Spasov; Pietro Liò (CoRR, 2020)

Computational Logic for Biomedicine and Neurosciences. - Abdorrahim Bahrami; Elisabetta De Maria; Joëlle Despeyroux; Amy P. Felty; Pietro Lió; Carlos Olarte (CoRR, 2020)

GRADE: Graph Dynamic Embedding. - Simeon E. Spasov; Alessandro Di Stefano; Pietro Liò; Jian Tang 005 (CoRR, 2020)

Graph representation forecasting of patient's medical conditions: towards a digital twin. - Pietro Barbiero; Ramón Viñas Torné 001; Pietro Lió (CoRR, 2020)

Learned Low Precision Graph Neural Networks. - Yiren Zhao; Duo Wang; Daniel Bates; Robert D. Mullins; Mateja Jamnik; Pietro Liò (CoRR, 2020)

Message Passing Neural Processes. - Ben Day; Catalina Cangea; Arian R. Jamasb; Pietro Liò (CoRR, 2020)

The Role of Isomorphism Classes in Multi-Relational Datasets. - Vijja Wichitwechkarn; Ben Day; Cristian Bodnar; Matthew Wales; Pietro Liò (CoRR, 2020)

Incorporating network based protein complex discovery into automated model construction. - Paul Scherer; Maja Trebacz; Nikola Simidjievski; Zohreh Shams; Helena Andrés-Terré; Pietro Liò; Mateja Jamnik (CoRR, 2020)

Gene Regulatory Network Inference with Latent Force Models. - Jacob Moss; Pietro Lió (CoRR, 2020)

Using ontology embeddings for structural inductive bias in gene expression data analysis. - Maja Trebacz; Zohreh Shams; Mateja Jamnik; Paul Scherer; Nikola Simidjievski; Helena Andrés-Terré; Pietro Liò (CoRR, 2020)

MEME: Generating RNN Model Explanations via Model Extraction. - Dmitry Kazhdan; Botty Dimanov; Mateja Jamnik; Pietro Liò (CoRR, 2020)

A machine learning model to identify early stage symptoms of SARS-Cov-2 infected patients. - Md. Martuza Ahamad; Sakifa Aktar; Md Rashed-Al-Mahfuz; Shahadat Uddin; Pietro Liò; Haoming Xu; Matthew A. Summers; Julian M. W. Quinn; Mohammad Ali Moni (Expert Syst. Appl., 2020)

DADIM: A distance adjustment dynamic influence map model. - Xiaofeng Lu; Xiaoming Wang; Pietro Lio'; Pan Hui 001 (Future Gener. Comput. Syst., 2020)

PECLIDES Neuro: A Personalisable Clinical Decision Support System for Neurological Diseases. - Tamara Müller; Pietro Liò (Frontiers Artif. Intell., 2020)

Integrating Petri Nets and Flux Balance Methods in Computational Biology Models: a Methodological and Computational Practice. - Simone Pernice; Laura Follia; Gianfranco Balbo; Luciano Milanesi; Giulia Sartini; Niccoló Totis; Pietro Lió; Ivan Merelli; Francesca Cordero; Marco Beccuti (Fundam. Informaticae, 2020)

A Novel Methodology for designing Policies in Mobile Crowdsensing Systems. - Alessandro Di Stefano; Marialisa Scatà; Barbara Attanasio; Aurelio La Corte; Pietro Lió; Sajal K. Das 001 (Pervasive Mob. Comput., 2020)

XFlow: Cross-Modal Deep Neural Networks for Audiovisual Classification. - Catalina Cangea; Petar Velickovic; Pietro Liò (IEEE Trans. Neural Networks Learn. Syst., 2020)

pietrobarbiero/computational-patient: Absolutno. - Pietro Barbiero; Pietro Liò (Zenodo, 2020)

pietrobarbiero/digital-patient: Absolutno. - Pietro Barbiero; Ramón Viñas Torné 001; Pietro Liò (Zenodo, 2020)

Temporal pointwise convolutional networks for length of stay prediction in the intensive care unit. - Emma Rocheteau; Pietro Liò; Stephanie L. Hyland (CHIL, 2021)

Resilience learning through self adaptation in digital twins of human-cyber-physical systems. - Emanuele Bellini 001; Franco Bagnoli; Mauro Caporuscio; Ernesto Damiani; Francesco Flammini; Igor Linkov; Pietro Liò; Stefano Marrone 001 (CSR, 2021)

International Workshop On Application of Intelligent Technology in Security - AITS 2021. - Xiaofeng Lu; Pietro Liò (DSN Workshops, 2021)

Neural ODE Processes. - Alexander Norcliffe; Cristian Bodnar; Ben Day; Jacob Moss; Pietro Liò (ICLR, 2021)

Directional Graph Networks. - Dominique Beaini; Saro Passaro; Vincent Létourneau; William L. Hamilton; Gabriele Corso; Pietro Lió (ICML, 2021)

Weisfeiler and Lehman Go Topological: Message Passing Simplicial Networks. - Cristian Bodnar; Fabrizio Frasca; Yuguang Wang 001; Nina Otter; Guido F. Montúfar; Pietro Lió; Michael M. Bronstein (ICML, 2021)

How Framelets Enhance Graph Neural Networks. - Xuebin Zheng; Bingxin Zhou; Junbin Gao; Yuguang Wang 001; Pietro Lió; Ming Li 065; Guido Montúfar (ICML, 2021)

An Effective Loss Function for Generating 3D Models from Single 2D Image Without Rendering. - Nikola Zubic; Pietro Liò (AIAI, 2021)

Early Exit Ensembles for Uncertainty Quantification. - Lorena Qendro; Alexander Campbell; Pietro Liò; Cecilia Mascolo (ML4H@NeurIPS, 2021)

Multimodal Graph Coarsening for Interpretable, MRI-Based Brain Graph Neural Network. - Isaac Sebenius; Alexander Campbell; Sarah E. Morgan; Edward T. Bullmore; Pietro Liò (MLSP, 2021)

Weisfeiler and Lehman Go Cellular: CW Networks. - Cristian Bodnar; Fabrizio Frasca; Nina Otter; Yuguang Wang 001; Pietro Liò; Guido F. Montúfar; Michael M. Bronstein (NeurIPS, 2021)

Neural Distance Embeddings for Biological Sequences. - Gabriele Corso; Zhitao Ying; Michal Pándy; Petar Velickovic; Jure Leskovec; Pietro Liò (NeurIPS, 2021)

Emotion Recognition From EEG Signal Focusing on Deep Learning and Shallow Learning Techniques. - Md. Rabiul Islam 007; Mohammad Ali Moni; Md. Milon Islam; Md Rashed-Al-Mahfuz; Md. Saiful Islam 003; Md. Kamrul Hasan 002; Md. Sabir Hossain; Mohiuddin Ahmad; Shahadat Uddin; A. K. M. Azad; Salem A. Alyami; Md. Atiqur Rahman Ahad; et al. (IEEE Access, 2021)

Integration and interplay of machine learning and bioinformatics approach to identify genetic interaction related to ovarian cancer chemoresistance. - Kexin Chen 003; Haoming Xu; Yiming Lei; Pietro Lió; Yuan Li; Hongyan Guo; Mohammad Ali Moni (Briefings Bioinform., 2021)

Pathogenetic profiling of COVID-19 and SARS-like viruses. - Zulkar Nain; Humayan Kabir Rana; Pietro Liò; Sheikh Mohammed Shariful Islam; Matthew A. Summers; Mohammad Ali Moni (Briefings Bioinform., 2021)

Signal metrics analysis of oscillatory patterns in bacterial multi-omic networks. - Francesco Bardozzo; Pietro Lió; Roberto Tagliaferri (Bioinform., 2021)

Advantages of using graph databases to explore chromatin conformation capture experiments. - Daniele D'Agostino; Pietro Liò; Marco Aldinucci; Ivan Merelli (BMC Bioinform., 2021)

Analysis of single-cell RNA sequencing data based on autoencoders. - Andrea Tangherloni; Federico Ricciuti; Daniela Besozzi; Pietro Liò; Ana Cvejic (BMC Bioinform., 2021)

Predicting Patient Outcomes with Graph Representation Learning. - Emma Rocheteau; Catherine Tong; Petar Velickovic; Nicholas D. Lane; Pietro Liò (CoRR, 2021)

Adaptive Filters and Aggregator Fusion for Efficient Graph Convolutions. - Shyam A. Tailor; Felix L. Opolka; Pietro Liò; Nicholas D. Lane (CoRR, 2021)

Is Disentanglement all you need? Comparing Concept-based & Disentanglement Approaches. - Dmitry Kazhdan; Botty Dimanov; Helena Andrés-Terré; Mateja Jamnik; Pietro Liò; Adrian Weller (CoRR, 2021)

Meta-learning using privileged information for dynamics. - Ben Day; Alexander Norcliffe; Jacob Moss; Pietro Liò (CoRR, 2021)

MIASSR: An Approach for Medical Image Arbitrary Scale Super-Resolution. - Jin Zhu; Chuan Tan; Junwei Yang; Guang Yang 006; Pietro Lio' (CoRR, 2021)

Neural message passing for joint paratope-epitope prediction. - Alice Del Vecchio; Andreea Deac; Pietro Liò; Petar Velickovic (CoRR, 2021)

Attentional meta-learners are polythetic classifiers. - Ben Day; Ramón Viñas 001; Nikola Simidjievski; Pietro Liò (CoRR, 2021)

High Frequency EEG Artifact Detection with Uncertainty via Early Exit Paradigm. - Lorena Qendro; Alexander Campbell; Pietro Liò; Cecilia Mascolo (CoRR, 2021)

Graph Representation Learning on Tissue-Specific Multi-Omics. - Amine Amor; Pietro Lio'; Vikash Singh; Ramón Viñas Torné 001; Helena Andrés-Terré (CoRR, 2021)

GCExplainer: Human-in-the-Loop Concept-based Explanations for Graph Neural Networks. - Lucie Charlotte Magister; Dmitry Kazhdan; Vikash Singh; Pietro Liò (CoRR, 2021)

Modular Neural Ordinary Differential Equations. - Max Zhu; Pietro Lió; Jacob Moss (CoRR, 2021)

Approximate Latent Force Model Inference. - Jacob Moss; Felix L. Opolka; Bianca Dumitrascu; Pietro Lió (CoRR, 2021)

An investigation of pre-upsampling generative modelling and Generative Adversarial Networks in audio super resolution. - James King; Ramón Viñas Torné 001; Alexander Campbell; Pietro Liò (CoRR, 2021)

Structure-aware generation of drug-like molecules. - Pavol Drotár; Arian Rokkum Jamasb; Ben Day; Catalina Cangea; Pietro Liò (CoRR, 2021)

Fast T2w/FLAIR MRI Acquisition by Optimal Sampling of Information Complementary to Pre-acquired T1w MRI. - Junwei Yang; Xiao-Xin Li; Feihong Liu; Dong Nie; Pietro Liò; Haikun Qi; Dinggang Shen (CoRR, 2021)

Spectral Transform Forms Scalable Transformer. - Bingxin Zhou; Xinliang Liu; Yuehua Liu; Yunying Huang; Pietro Liò; Yuguang Wang 001 (CoRR, 2021)

Heavy-tailed denoising score matching. - Jacob Deasy; Nikola Simidjievski; Pietro Liò (CoRR, 2021)

AI-based Reconstruction for Fast MRI - A Systematic Review and Meta-analysis. - Yutong Chen; Carola-Bibiane Schönlieb; Pietro Liò; Tim Leiner; Pier Luigi Dragotti; Gerald Wang; Daniel Rueckert; David N. Firmin; Guang Yang 006 (CoRR, 2021)

Deep Graph Mapper: Seeing Graphs Through the Neural Lens. - Cristian Bodnar; Catalina Cangea; Pietro Liò (Frontiers Big Data, 2021)

Arbitrary Scale Super-Resolution for Medical Images. - Jin Zhu; Chuan Tan; Junwei Yang; Guang Yang 006; Pietro Lio' (Int. J. Neural Syst., 2021)

How artificial intelligence and machine learning can help healthcare systems respond to COVID-19. - Mihaela van der Schaar; Ahmed M. Alaa; R. Andres Floto; Alexander Gimson; Stefan Scholtes; Angela M. Wood; Eoin F. McKinney; Daniel Jarrett; Pietro Lió; Ari Ercole (Mach. Learn., 2021)

A Fine-Grained IoT Data Access Control Scheme Combining Attribute-Based Encryption and Blockchain. - Xiaofeng Lu; Songbing Fu; Cheng Jiang 009; Pietro Lió (Secur. Commun. Networks, 2021)

A Multiplex Social Contagion Dynamics Model to Shape and Discriminate D2D Content Dissemination. - Marialisa Scatà; Alessandro Di Stefano; Aurelio La Corte; Pietro Liò (IEEE Trans. Cogn. Commun. Netw., 2021)

Entropy-Based Logic Explanations of Neural Networks. - Pietro Barbiero; Gabriele Ciravegna; Francesco Giannini; Pietro Lió; Marco Gori; Stefano Melacci (AAAI, 2022)

Algorithmic Concept-Based Explainable Reasoning. - Dobrik Georgiev; Pietro Barbiero; Dmitry Kazhdan; Petar Velickovic; Pietro Lió (AAAI, 2022)

Bayesian Link Prediction with Deep Graph Convolutional Gaussian Processes. - Felix L. Opolka; Pietro Liò (AISTATS, 2022)

Adaptive Gaussian Processes on Graphs via Spectral Graph Wavelets. - Felix L. Opolka; Yin-Cong Zhi; Pietro Liò; Xiaowen Dong 001 (AISTATS, 2022)

Poster: CFMAP: A Robust CPU Clock Fingerprint Model for Device Authentication. - Xiaofeng Lu; Renyu Pang; Pietro Liò (CCS, 2022)

Explainer Divergence Scores (EDS): Some Post-Hoc Explanations May be Effective for Detecting Unknown Spurious Correlations. - Shea Cardozo; Gabriel Islas Montero; Dmitry Kazhdan; Botty Dimanov; Maleakhi A. Wijaya; Mateja Jamnik; Pietro Liò (CIKM Workshops, 2022)

Extending Logic Explained Networks to Text Classification. - Rishabh Jain; Gabriele Ciravegna; Pietro Barbiero; Francesco Giannini; Davide Buffelli; Pietro Liò (EMNLP, 2022)

Robust and Efficient Uncertainty Aware Biosignal Classification via Early Exit Ensembles. - Alexander Campbell; Lorena Qendro; Pietro Liò; Cecilia Mascolo (ICASSP, 2022)

Do We Need Anisotropic Graph Neural Networks? - Shyam A. Tailor; Felix L. Opolka; Pietro Liò; Nicholas Donald Lane (ICLR, 2022)

Context Correlation Aware Network for Cardiac Segmentation. - Junchao Fan; Jiawei Pei; Xiuli Bi; Bin Xiao 002; Pietro Liò (ICME, 2022)

Attentional Meta-learners for Few-shot Polythetic Classification. - Ben J. Day; Ramón Viñas Torné 001; Nikola Simidjievski; Pietro Lió (ICML, 2022)

3D Infomax improves GNNs for Molecular Property Prediction. - Hannes Stärk; Dominique Beaini; Gabriele Corso; Prudencio Tossou; Christian Dallago; Stephan Günnemann; Pietro Lió (ICML, 2022)

Continuous Neural Algorithmic Planners. - Yu He; Petar Velickovic; Pietro Liò; Andreea Deac (LoG, 2022)

Learning Graph Search Heuristics. - Michal Pándy; Weikang Qiu; Gabriele Corso; Petar Velickovic; Zhitao Ying; Jure Leskovec; Pietro Liò (LoG, 2022)

Distributed Representations of Graphs for Drug Pair Scoring. - Paul Scherer; Pietro Liò; Mateja Jamnik (LoG, 2022)

Well-Conditioned Spectral Transforms for Dynamic Graph Representation. - Bingxin Zhou; Xinliang Liu; Yuehua Liu; Yunying Huang; Pietro Liò; Yuguang Wang 001 (LoG, 2022)

Joint Group-Wise Motion Estimation and Segmentation of Cardiac Cine MR Images Using Recurrent U-Net. - Pengfang Qian; Junwei Yang; Pietro Lió; Peng Hu; Haikun Qi (MIUA, 2022)

Robust android malware detection based on subgraph network and denoising GCN network. - Xiaofeng Lu; Jinglun Zhao; Pietro Lió (MobiSys, 2022)

Neural Sheaf Diffusion: A Topological Perspective on Heterophily and Oversmoothing in GNNs. - Cristian Bodnar; Francesco Di Giovanni; Benjamin Paul Chamberlain; Pietro Lió; Michael M. Bronstein (NeurIPS, 2022)

SizeShiftReg: a Regularization Method for Improving Size-Generalization in Graph Neural Networks. - Davide Buffelli; Pietro Lió; Fabio Vandin (NeurIPS, 2022)

Graph Neural Networks with Adaptive Readouts. - David Buterez; Jon Paul Janet; Steven J. Kiddle; Dino Oglic; Pietro Liò (NeurIPS, 2022)

Composite Feature Selection Using Deep Ensembles. - Fergus Imrie; Alexander Norcliffe; Pietro Lió; Mihaela van der Schaar (NeurIPS, 2022)

Graphein - a Python Library for Geometric Deep Learning and Network Analysis on Biomolecular Structures and Interaction Networks. - Arian R. Jamasb; Ramón Viñas Torné 001; Eric Ma; Yuanqi Du; Charles Harris; Kexin Huang; Dominic Hall; Pietro Lió; Tom L. Blundell (NeurIPS, 2022)

Concept Embedding Models: Beyond the Accuracy-Explainability Trade-Off. - Mateo Espinosa Zarlenga; Pietro Barbiero; Gabriele Ciravegna; Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Zohreh Shams; Frédéric Precioso; Stefano Melacci; Adrian Weller; Pietro Lió; Mateja Jamnik (NeurIPS, 2022)

Sheaf Neural Networks with Connection Laplacians. - Federico Barbero; Cristian Bodnar; Haitz Sáez de Ocáriz Borde; Michael M. Bronstein; Petar Velickovic; Pietro Liò (TAG-ML, 2022)

APPROXIMATE EQUIVARIANCE SO(3) NEEDLET CONVOLUTION. - Kai Yi; Jialin Chen; Yu Guang Wang 001; Bingxin Zhou; Pietro Liò; Yanan Fan; Jan Hamann (TAG-ML, 2022)

You only Look at Patches: A Patch-wise Framework for 3D Unsupervised Medical Image Registration. - Lihao Liu; Zhening Huang; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (WBIR, 2022)

CellVGAE: an unsupervised scRNA-seq analysis workflow with graph attention networks. - David Buterez; Ioana Bica; Ifrah Tariq; Helena Andrés-Terré; Pietro Liò (Bioinform., 2022)

Unsupervised construction of computational graphs for gene expression data with explicit structural inductive biases. - Paul Scherer; Maja Trebacz; Nikola Simidjievski; Ramón Viñas 001; Zohreh Shams; Helena Andrés-Terré; Mateja Jamnik; Pietro Liò (Bioinform., 2022)

Adversarial generation of gene expression data. - Ramón Viñas 001; Helena Andrés-Terré; Pietro Liò; Kevin Bryson 001 (Bioinform., 2022)

NEPTUNE: A novel computational approach for accurate and large-scale identification of tumor homing peptides. - Phasit Charoenkwan; Nalini Schaduangrat; Pietro Lio'; Mohammad Ali Moni; Balachandran Manavalan; Watshara Shoombuatong (Comput. Biol. Medicine, 2022)

SAPPHIRE: A stacking-based ensemble learning framework for accurate prediction of thermophilic proteins. - Phasit Charoenkwan; Nalini Schaduangrat; Mohammad Ali Moni; Pietro Lio'; Balachandran Manavalan; Watshara Shoombuatong (Comput. Biol. Medicine, 2022)

Spatio-temporal Vision Transformer for Super-resolution Microscopy. - Charles N. Christensen; Meng Lu; Edward N. Ward; Pietro Liò; Clemens F. Kaminski (CoRR, 2022)

PC-SwinMorph: Patch Representation for Unsupervised Medical Image Registration and Segmentation. - Lihao Liu; Zhening Huang; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2022)

Data and Physics Driven Learning Models for Fast MRI - Fundamentals and Methodologies from CNN, GAN to Attention and Transformers. - Jiahao Huang; Yingying Fang; Yang Nan 002; Huanjun Wu; Yinzhe Wu 001; Zhifan Gao; Yang Li 010; Zidong Wang 001; Pietro Liò; Daniel Rueckert; Yonina C. Eldar; Guang Yang 006 (CoRR, 2022)

Simplicial Attention Networks. - Christopher Wei Jin Goh; Cristian Bodnar; Pietro Liò (CoRR, 2022)

Classification of datasets with imputed missing values: does imputation quality matter? - Tolou Shadbahr; Michael Roberts; Jan Stanczuk; Julian D. Gilbey; Philip Teare; Sören Dittmer; Matthew Thorpe; Ramón Viñas Torné 001; Evis Sala; Pietro Lió; Mishal Patel; AIX-COVNET Collaboration; et al. (CoRR, 2022)

Encoding Concepts in Graph Neural Networks. - Lucie Charlotte Magister; Pietro Barbiero; Dmitry Kazhdan; Federico Siciliano; Gabriele Ciravegna; Fabrizio Silvestri; Pietro Liò; Mateja Jamnik (CoRR, 2022)

Concept Embedding Models. - Mateo Espinosa Zarlenga; Pietro Barbiero; Gabriele Ciravegna; Giuseppe Marra; Francesco Giannini; Michelangelo Diligenti; Zohreh Shams; Frédéric Precioso; Stefano Melacci; Adrian Weller; Pietro Liò; Mateja Jamnik (CoRR, 2022)

Structure-based Drug Design with Equivariant Diffusion Models. - Arne Schneuing; Yuanqi Du; Charles Harris; Arian R. Jamasb; Ilia Igashov; Weitao Du; Tom L. Blundell; Pietro Lió; Carla Gomes 001; Max Welling; Michael M. Bronstein; Bruno E. Correia (CoRR, 2022)

Graph-Conditioned MLP for High-Dimensional Tabular Biomedical Data. - Andrei Margeloiu; Nikola Simidjievski; Pietro Lio'; Mateja Jamnik (CoRR, 2022)

Goal-Conditioned Reinforcement Learning in the Presence of an Adversary. - Carlos Purves; Pietro Liò; Catalina Cangea (CoRR, 2022)

Discrete Lagrangian Neural Networks with Automatic Symmetry Discovery. - Yana Lishkova; Paul Scherer; Steffen Ridderbusch; Mateja Jamnik; Pietro Liò; Sina Ober-Blöbaum; Christian Offen (CoRR, 2022)

Transductive Kernels for Gaussian Processes on Graphs. - Yin-Cong Zhi; Felix L. Opolka; Yin Cheng Ng; Pietro Liò; Xiaowen Dong 001 (CoRR, 2022)

Learning Feynman Diagrams using Graph Neural Networks. - Harrison Mitchell; Alexander Norcliffe; Pietro Liò (CoRR, 2022)

A physics-informed search for metric solutions to Ricci flow, their embeddings, and visualisation. - Aarjav Jain; Challenger Mishra; Pietro Liò (CoRR, 2022)

A novel interpretable machine learning algorithm to identify optimal parameter space for cancer growth. - Helena Coggan; Helena Andrés-Terré; Pietro Liò (Frontiers Big Data, 2022)

Multimodal and multicontrast image fusion via deep generative models. - Giovanna Maria Dimitri; Simeon E. Spasov; Andrea Duggento; Luca Passamonti; Pietro Lió; Nicola Toschi (Inf. Fusion, 2022)

Heterogeneous Model Fusion Federated Learning Mechanism Based on Model Mapping. - Xiaofeng Lu; Yuying Liao; Chao Liu; Pietro Liò; Pan Hui 001 (IEEE Internet Things J., 2022)

Improved prediction and characterization of blood-brain barrier penetrating peptides using estimated propensity scores of dipeptides. - Phasit Charoenkwan; Pramote Chumnanpuen; Nalini Schaduangrat; Pietro Lio'; Mohammad Ali Moni; Watshara Shoombuatong (J. Comput. Aided Mol. Des., 2022)

A deep graph neural network architecture for modelling spatio-temporal dynamics in resting-state functional MRI data. - Tiago Azevedo; Alexander Campbell; Rafael Romero-Garcia; Luca Passamonti; Richard A. I. Bethlehem; Pietro Liò; Nicola Toschi (Medical Image Anal., 2022)

Guest Editorial: Non-Euclidean Machine Learning. - Stefanos Zafeiriou; Michael M. Bronstein; Taco Cohen; Oriol Vinyals; Le Song; Jure Leskovec; Pietro Liò; Joan Bruna; Marco Gori (IEEE Trans. Pattern Anal. Mach. Intell., 2022)

AI-Based Reconstruction for Fast MRI - A Systematic Review and Meta-Analysis. - Yutong Chen; Carola-Bibiane Schönlieb; Pietro Liò; Tim Leiner; Pier Luigi Dragotti; Ge Wang 001; Daniel Rueckert; David N. Firmin; Guang Yang 006 (Proc. IEEE, 2022)

System Neural Network: Evolution and Change Based Structure Learning. - Animesh Chaturvedi 001; Aruna Tiwari; Shubhangi Chaturvedi; Pietro Liò (IEEE Trans. Artif. Intell., 2022)

Weight Predictor Network with Feature Selection for Small Sample Tabular Biomedical Data. - Andrei Margeloiu; Nikola Simidjievski; Pietro Liò; Mateja Jamnik (AAAI, 2023)

Global Concept-Based Interpretability for Graph Neural Networks via Neuron Analysis. - Han Xuanyuan; Pietro Barbiero; Dobrik Georgiev; Lucie Charlotte Magister; Pietro Liò (AAAI, 2023)

SurvivalGAN: Generating Time-to-Event Data for Survival Analysis. - Alexander Norcliffe; Bogdan Cebere; Fergus Imrie; Pietro Liò; Mihaela van der Schaar (AISTATS, 2023)

A Rewiring Contrastive Patch PerformerMixer Framework for Graph Representation Learning. - Zhongtian Sun; Anoushka Harit; Alexandra I. Cristea; Jingyun Wang; Pietro Lio (IEEE Big Data, 2023)

Synergy Between Mechanistic Modelling and Ensemble Feature Selection Approaches to Explore Multiscale Biological Heterogeneity. - Riccardo Aucello; Nicola Licheri; Elena Rosso; Giulio Ferrero; Sandro Gepiro Contaldo; Simone Pernice; Pietro Lió; Francesca Cordero; Marco Beccuti (CIBB, 2023)

MMCTNet: Multi-Modal Cony-Transformer Network for Predicting Good and Poor Outcomes in Cardiac Arrest Patients. - Xiuli Bi; Shizhan Tang; Zonglin Yang; Xin Deng; Bin Xiao 002; Pietro Liò (CinC, 2023)

SCOTCH and SODA: A Transformer Video Shadow Detection Framework. - Lihao Liu; Jean Prost; Lei Zhu 003; Nicolas Papadakis; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CVPR, 2023)

Topological Network Traffic Compression. - Guillermo Bernárdez; Lev Telyatnikov; Eduard Alarcón; Albert Cabellos-Aparicio; Pere Barlet-Ros; Pietro Liò (GNNet@CoNEXT, 2023)

Global Explainability of GNNs via Logic Combination of Learned Concepts. - Steve Azzolin; Antonio Longa; Pietro Barbiero; Pietro Liò; Andrea Passerini (ICLR, 2023)

Latent Graph Inference using Product Manifolds. - Haitz Sáez de Ocáriz Borde; Anees Kazi; Federico Barbero; Pietro Liò (ICLR, 2023)

Adaptive Distance Message Passing From the Multi-Relational Edge View. - Zhongtian Sun; Alexandra I. Cristea; Pietro Lio; Jialin Yu (Tiny Papers @ ICLR, 2023)

Interpretable Neural-Symbolic Concept Reasoning. - Pietro Barbiero; Gabriele Ciravegna; Francesco Giannini; Mateo Espinosa Zarlenga; Lucie Charlotte Magister; Alberto Tonda; Pietro Lio; Frédéric Precioso; Mateja Jamnik; Giuseppe Marra (ICML, 2023)

On Over-Squashing in Message Passing Neural Networks: The Impact of Width, Depth, and Topology. - Francesco Di Giovanni; Lorenzo Giusti; Federico Barbero; Giulia Luise; Pietro Lio; Michael M. Bronstein (ICML, 2023)

On the Expressive Power of Geometric Graph Neural Networks. - Chaitanya K. Joshi; Cristian Bodnar; Simon V. Mathis; Taco Cohen; Pietro Lio (ICML, 2023)

Neural Algorithmic Reasoning for Combinatorial Optimisation. - Dobrik Georgiev; Danilo Numeroso; Davide Bacciu; Pietro Lio (LoG, 2023)

Will More Expressive Graph Neural Networks Do Better on Generative Tasks? - Xiandong Zou; Xiangyu Zhao; Pietro Lio; Yiren Zhao (LoG, 2023)

DBGDGM: Dynamic Brain Graph Deep Generative Model. - Alexander Campbell; Simeon Emilov Spasov; Nicola Toschi; Pietro Lio (MIDL, 2023)

DBGSL: Dynamic Brain Graph Structure Learning. - Alexander Campbell; Antonio Giuliano Zippo; Luca Passamonti; Nicola Toschi; Pietro Lio (MIDL, 2023)

From charts to atlas: Merging latent spaces into one. - Donato Crisostomi; Irene Cannistraci; Luca Moschella; Pietro Barbiero; Marco Ciccone; Pietro Liò; Emanuele Rodolà (NeurReps, 2023)

Sheaf-based Positional Encodings for Graph Neural Networks. - Yu He; Cristian Bodnar; Pietro Liò (NeurReps, 2023)

AMES: A differentiable embedding space selection framework for latent graph inference. - Yuan Lu; Haitz Sáez de Ocáriz Borde; Pietro Liò (NeurReps, 2023)

Sheaf Hypergraph Networks. - Iulia Duta; Giulia Cassarà; Fabrizio Silvestri; Pietro Lió (NeurIPS, 2023)

Interpretable Graph Networks Formulate Universal Algebra Conjectures. - Francesco Giannini; Stefano Fioravanti; Oguzhan Keskin; Alisia Maria Lupidi; Lucie Charlotte Magister; Pietro Lió; Pietro Barbiero (NeurIPS, 2023)

Graph Denoising Diffusion for Inverse Protein Folding. - Kai Yi; Bingxin Zhou; Yiqing Shen 003; Pietro Lió; Yuguang Wang 001 (NeurIPS, 2023)

Bridging Equational Properties and Patterns on Graphs: an AI-Based Approach. - Oguzhan Keskin; Alisia Maria Lupidi; Stefano Fioravanti; Lucie Charlotte Magister; Pietro Barbiero; Pietro Lio; Francesco Giannini (TAG-ML, 2023)

Graph classification Gaussian processes via spectral features. - Felix L. Opolka; Yin-Cong Zhi; Pietro Liò; Xiaowen Dong 001 (UAI, 2023)

Explainable Depression Detection Using Handwriting Features. - Francesco Prinzi; Gennaro Raimo; Pietro Barbiero; Gennaro Cordasco; Pietro Liò; Salvatore Vitabile; Anna Esposito (WIRN, 2023)

GAT-DNS: DNS Multivariate Time Series Prediction Model Based on Graph Attention Network. - Xiaofeng Lu; Xiaoyu Zhang; Pietro Lió (WWW (Companion Volume), 2023)

A Federated Learning Benchmark for Drug-Target Interaction. - Gianluca Mittone; Filip Svoboda; Marco Aldinucci; Nicholas D. Lane; Pietro Lió (WWW (Companion Volume), 2023)

Concept Distillation in Graph Neural Networks. - Lucie Charlotte Magister; Pietro Barbiero; Dmitry Kazhdan; Federico Siciliano; Gabriele Ciravegna; Fabrizio Silvestri; Mateja Jamnik; Pietro Liò (xAI (3), 2023)

Logic Explained Networks. - Gabriele Ciravegna; Pietro Barbiero; Francesco Giannini; Marco Gori; Pietro Liò; Marco Maggini; Stefano Melacci (Artif. Intell., 2023)

PSRTTCA: A new approach for improving the prediction and characterization of tumor T cell antigens using propensity score representation learning. - Phasit Charoenkwan; Chonlatip Pipattanaboon; Chanin Nantasenamat; Md. Mehedi Hasan 002; Mohammad Ali Moni; Pietro Lio'; Watshara Shoombuatong (Comput. Biol. Medicine, 2023)

A Comprehensive Survey of Graph-level Learning. - Zhenyu Yang 004; Ge Zhang 002; Jia Wu 001; Jian Yang 001; Quan Z. Sheng; Shan Xue 001; Chuan Zhou 001; Charu C. Aggarwal; Hao Peng 001; Wenbin Hu 001; Edwin R. Hancock; Pietro Liò (CoRR, 2023)

Task-Agnostic Graph Neural Network Evaluation via Adversarial Collaboration. - Xiangyu Zhao; Hannes Stärk; Dominique Beaini; Pietro Liò; Yiren Zhao (CoRR, 2023)

GCI: A (G)raph (C)oncept (I)nterpretation Framework. - Dmitry Kazhdan; Botty Dimanov; Lucie Charlotte Magister; Pietro Barbiero; Mateja Jamnik; Pietro Liò (CoRR, 2023)

A Federated Learning Benchmark for Drug-Target Interaction. - Filip Svoboda; Gianluca Mittone; Nicholas D. Lane; Pietro Liò (CoRR, 2023)

A residual dense vision transformer for medical image super-resolution with segmentation-based perceptual loss fine-tuning. - Jin Zhu; Guang Yang 006; Pietro Liò (CoRR, 2023)

Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing. - Mehedi Hasan; Moloud Abdar; Abbas Khosravi; Uwe Aickelin; Pietro Lio'; Ibrahim Hossain; Ashikur Rahman; Saeid Nahavandi (CoRR, 2023)

Assisting clinical practice with fuzzy probabilistic decision trees. - Emma L. Ambags; Giulia Capitoli; Vincenzo L' Imperio; Michele Provenzano; Marco S. Nobile; Pietro Liò (CoRR, 2023)

Sheaf Neural Networks for Graph-based Recommender Systems. - Antonio Purificato; Giulia Cassarà; Pietro Liò; Fabrizio Silvestri (CoRR, 2023)

ElegansNet: a brief scientific report and initial experiments. - Francesco Bardozzo; Andrea Terlizzi; Pietro Liò; Roberto Tagliaferri (CoRR, 2023)

Categorical Foundations of Explainable AI: A Unifying Formalism of Structures and Semantics. - Pietro Barbiero; Stefano Fioravanti; Francesco Giannini; Alberto Tonda; Pietro Liò; Elena Di Lavore (CoRR, 2023)

Learning Linear Embeddings for Non-Linear Network Dynamics with Koopman Message Passing. - King Fai Yeh; Paris D. L. Flood; William Redman; Pietro Liò (CoRR, 2023)

Deep Multiple Instance Learning with Distance-Aware Self-Attention. - Georg Wölflein; Lucie Charlotte Magister; Pietro Liò; David J. Harrison; Ognjen Arandjelovic (CoRR, 2023)

Multi-State RNA Design with Geometric Multi-Graph Neural Networks. - Chaitanya K. Joshi; Arian R. Jamasb; Ramón Viñas 001; Charles Harris; Simon V. Mathis; Pietro Liò (CoRR, 2023)

Group Invariant Global Pooling. - Kamil Bujel; Yonatan Gideoni; Chaitanya K. Joshi; Pietro Liò (CoRR, 2023)

Renormalized Graph Neural Networks. - Francesco Caso; Giovanni Trappolini; Andrea Bacciu; Pietro Liò; Fabrizio Silvestri (CoRR, 2023)

A Feature Reuse Framework with Texture-adaptive Aggregation for Reference-based Super-Resolution. - Xiaoyong Mei; Yi Yang; Ming Li 065; Changqin Huang; Kai Zhang; Pietro Lió (CoRR, 2023)

Impact of the Covid 19 outbreaks on the italian twitter vaccination debat: a network based analysis. - Veronica Lachi; Giovanna Maria Dimitri; Alessandro Di Stefano; Pietro Liò; Monica Bianchini; Chiara Mocenni (CoRR, 2023)

CIN++: Enhancing Topological Message Passing. - Lorenzo Giusti; Teodora Reu; Francesco Ceccarelli; Cristian Bodnar; Pietro Liò (CoRR, 2023)

Neural Embeddings for Protein Graphs. - Francesco Ceccarelli; Lorenzo Giusti; Sean B. Holden; Pietro Liò (CoRR, 2023)

Interpretable Medical Diagnostics with Structured Data Extraction by Large Language Models. - Aleksa Bisercic; Mladen Nikolic; Mihaela van der Schaar; Boris Delibasic; Pietro Liò; Andrija Petrovic (CoRR, 2023)

Hybrid Graph: A Unified Graph Representation with Datasets and Benchmarks for Complex Graphs. - Zehui Li; Xiangyu Zhao; Mingzhu Shen; Guy-Bart Stan; Pietro Liò; Yiren Zhao (CoRR, 2023)

SHARCS: Shared Concept Space for Explainable Multimodal Learning. - Gabriele Dominici; Pietro Barbiero; Lucie Charlotte Magister; Pietro Liò; Nikola Simidjievski (CoRR, 2023)

Neural Priority Queues for Graph Neural Networks. - Rishabh Jain; Petar Velickovic; Pietro Liò (CoRR, 2023)

Topological Graph Signal Compression. - Guillermo Bernárdez; Lev Telyatnikov; Eduard Alarcón; Albert Cabellos-Aparicio; Pere Barlet-Ros; Pietro Liò (CoRR, 2023)

Graph Neural Stochastic Differential Equations. - Richard Bergna; Felix L. Opolka; Pietro Liò; José Miguel Hernández-Lobato (CoRR, 2023)

A 3D explainability framework to uncover learning patterns and crucial sub-regions in variable sulci recognition. - Michail Mamalakis; Héloïse de Vareilles; Atheer AI-Manea; Samantha C. Mitchell; Ingrid Agartz; Lynn Egeland Morch-Johnsen; Jane R. Garrison; Jon S. Simons; Pietro Lio; John Suckling; Graham K. Murray (CoRR, 2023)

Unsupervised Fact Verification by Language Model Distillation. - Adrián Bazaga; Pietro Liò; Gos Micklem (CoRR, 2023)

SQLformer: Deep Auto-Regressive Query Graph Generation for Text-to-SQL Translation. - Adrián Bazaga; Pietro Liò; Gos Micklem (CoRR, 2023)

Dirichlet Energy Enhancement of Graph Neural Networks by Framelet Augmentation. - Jialin Chen; Yuelin Wang; Cristian Bodnar; Rex Ying; Pietro Lio; Yuguang Wang 001 (CoRR, 2023)

Traffic Video Object Detection using Motion Prior. - Lihao Liu; Yanqi Cheng; Dongdong Chen 004; Jing He; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2023)

Incorporating LLM Priors into Tabular Learners. - Max Zhu; Sinisa Stanivuk; Andrija Petrovic; Mladen Nikolic; Pietro Lio (CoRR, 2023)

TRIDENT: The Nonlinear Trilogy for Implicit Neural Representations. - Zhenda Shen; Yanqi Cheng; Raymond H. Chan; Pietro Liò; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2023)

Everybody Needs a Little HELP: Explaining Graphs via Hierarchical Concepts. - Jonas Jürß; Lucie Charlotte Magister; Pietro Barbiero; Pietro Liò; Nikola Simidjievski (CoRR, 2023)

Fourier Neural Differential Equations for learning Quantum Field Theories. - Isaac Brant; Alexander Norcliffe; Pietro Liò (CoRR, 2023)

Improving embedding of graphs with missing data by soft manifolds. - Andrea Marinoni; Pietro Lio'; Alessandro Barp; Christian Jutten; Mark Girolami (CoRR, 2023)

An Effective Universal Polynomial Basis for Spectral Graph Neural Networks. - Keke Huang; Pietro Liò (CoRR, 2023)

TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios. - Lihao Liu; Yanqi Cheng; Zhongying Deng; Shujun Wang; Dongdong Chen 004; Xiaowei Hu 001; Pietro Liò; Carola-Bibiane Schönlieb; Angelica E. Avilés-Rivero (CoRR, 2023)

Dual-Domain Multi-Contrast MRI Reconstruction with Synthesis-based Fusion Network. - Junwei Yang; Pietro Liò (CoRR, 2023)

Unsupervised Adaptive Implicit Neural Representation Learning for Scan-Specific MRI Reconstruction. - Junwei Yang; Pietro Liò (CoRR, 2023)

Digital Histopathology with Graph Neural Networks: Concepts and Explanations for Clinicians. - Alessandro Farace di Villaforesta; Lucie Charlotte Magister; Pietro Barbiero; Pietro Liò (CoRR, 2023)

A Hitchhiker's Guide to Geometric GNNs for 3D Atomic Systems. - Alexandre Duval; Simon V. Mathis; Chaitanya K. Joshi; Victor Schmidt; Santiago Miret; Fragkiskos D. Malliaros; Taco Cohen; Pietro Lio; Yoshua Bengio; Michael M. Bronstein (CoRR, 2023)

A framework for conditional diffusion modelling with applications in motif scaffolding for protein design. - Kieran Didi; Francisco Vargas 001; Simon V. Mathis; Vincent Dutordoir; Emile Mathieu; Urszula Julia Komorowska; Pietro Lio (CoRR, 2023)

Modular Multi-Source Prediction of Drug Side-Effects With DruGNN. - Pietro Bongini; Franco Scarselli; Monica Bianchini; Giovanna Maria Dimitri; Niccolò Pancino; Pietro Lió (IEEE ACM Trans. Comput. Biol. Bioinform., 2023)

Graph Neural Networks for Temporal Graphs: State of the Art, Open Challenges, and Opportunities. - Antonio Longa; Veronica Lachi; Gabriele Santin; Monica Bianchini; Bruno Lepri; Pietro Lio; Franco Scarselli; Andrea Passerini (Trans. Mach. Learn. Res., 2023)

Learning Logic Explanations by Neural Networks. - Gabriele Ciravegna; Francesco Giannini; Pietro Barbiero; Marco Gori; Pietro Lio; Marco Maggini; Stefano Melacci (Compendium of Neurosymbolic Artificial Intelligence, 2023)

MONEY: Ensemble learning for stock price movement prediction via a convolutional network with adversarial hypergraph model. - Zhongtian Sun; Anoushka Harit; Alexandra I. Cristea; Jingyun Wang; Pietro Lio (AI Open, 2023)

Controlling highway toll stations using deep learning, queuing theory, and differential evolution. - Andrija Petrovic; Mladen Nikolic; Ugljesa Bugaric; Boris Delibasic; Pietro Liò (Eng. Appl. Artif. Intell., 2023)

Hypergraph Factorisation Expression Quantitative Trait Loci. - Ramón Viñas 001; Chaitanya K. Joshi; Dobrik Georgiev; Phillip Lin; Bianca Dumitrascu; Pietro Liò; Eric R. Gamazon (Zenodo, 2023)

MF-PCBA: Multifidelity High-Throughput Screening Benchmarks for Drug Discovery and Machine Learning. - David Buterez; Jon Paul Janet; Steven J. Kiddle; Pietro Liò (J. Chem. Inf. Model., 2023)

HARDC : A novel ECG-based heartbeat classification method to detect arrhythmia using hierarchical attention based dual structured RNN with dilated CNN. - Md. Shofiqul Islam; Khondokar Fida Hasan; Sunjida Sultana; Shahadat Uddin; Pietro Lio'; Julian M. W. Quinn; Mohammad Ali Moni (Neural Networks, 2023)

Fast Multi-Contrast MRI Acquisition by Optimal Sampling of Information Complementary to Pre-Acquired MRI Contrast. - Junwei Yang; Xiao-Xin Li; Feihong Liu; Dong Nie; Pietro Liò; Haikun Qi; Dinggang Shen (IEEE Trans. Medical Imaging, 2023)

An LTE Authentication and Key Agreement Protocol Based on the ECC Self-Certified Public Key. - Xiaofeng Lu; Fan Yang; Luwen Zou; Pietro Liò; Pan Hui 001 (IEEE/ACM Trans. Netw., 2023)

Navigating the development challenges in creating complex data systems. - Sören Dittmer; Michael Roberts; Julian D. Gilbey; Ander Biguri; Ian Selby; Anna Breger; Matthew Thorpe; Jonathan R. Weir-McCall; Effrossyni Gkrania-Klotsas; Anna Korhonen; Emily R. Jefferson; Georg Langs; et al. (Nat. Mac. Intell., 2023)

Hypergraph factorization for multi-tissue gene expression imputation. - Ramón Viñas 001; Chaitanya K. Joshi; Dobrik Georgiev; Phillip Lin; Bianca Dumitrascu; Eric R. Gamazon; Pietro Liò (Nat. Mac. Intell., 2023)

StackFBAs: Detection of fetal brain abnormalities using CNN with stacking strategy from MRI images. - Anjir Ahmed Chowdhury; S. M. Hasan Mahmud; Khadija Kubra Shahjalal Hoque; Kawsar Ahmed; Francis M. Bui; Pietro Lio; Mohammad Ali Moni; Fahad Ahmed Al-Zahrani (J. King Saud Univ. Comput. Inf. Sci., 2023)

Surformer: An interpretable pattern-perceptive survival transformer for cancer survival prediction from histopathology whole slide images. - Zhikang Wang; Qian Gao; Xiaoping Yi; Xinyu Zhang 017; Yiwen Zhang; Daokun Zhang; Pietro Liò; Chris Bain; Richard Bassed; Shanshan Li; Yuming Guo 001; Seiya Imoto; et al. (Comput. Methods Programs Biomed., 2023)

RLPTO: A Reinforcement Learning-Based Performance-Time Optimized Task and Resource Scheduling Mechanism for Distributed Machine Learning. - Xiaofeng Lu; Chao Liu; Senhao Zhu; Yilu Mao; Pietro Lio; Pan Hui 001 (IEEE Trans. Parallel Distributed Syst., 2023)

TourSynbio: A Multi-Modal Large Model and Agent Framework to Bridge Text and Protein Sequences for Protein Engineering. - Yiqing Shen 003; Zan Chen; Michail Mamalakis; Yungeng Liu; Tianbin Li; Yanzhou Su; Junjun He; Pietro Liò; Yu Guang Wang 001 (BIBM, 2024)

FP-Elegans M1: Feature Pyramid Reservoir Connectome Transformers and Multi-backbone Feature Extractors for MEDMNIST2D-V2. - Francesco Bardozzo; Pierpaolo Fiore; Pietro Liò; Roberto Tagliaferri (CIBB, 2024)

Enhancing Node Representations for Real-World Complex Networks with Topological Augmentation. - Xiangyu Zhao; Zehui Li; Mingzhu Shen; Guy-Bart Stan; Pietro Liò; Yiren Zhao (ECAI, 2024)

HyperBERT: Mixing Hypergraph-Aware Layers with Language Models for Node Classification on Text-Attributed Hypergraphs. - Adrián Bazaga; Pietro Lio; Gos Micklem (EMNLP (Findings), 2024)

Language Model Knowledge Distillation for Efficient Question Answering in Spanish. - Adrián Bazaga; Pietro Lio; Gos Micklem (Tiny Papers @ ICLR, 2024)

Unsupervised Pretraining for Fact Verification by Language Model Distillation. - Adrián Bazaga; Pietro Lio; Gos Micklem (ICLR, 2024)

Evaluating Representation Learning on the Protein Structure Universe. - Arian Rokkum Jamasb; Alex Morehead; Chaitanya K. Joshi; Zuobai Zhang; Kieran Didi; Simon V. Mathis; Charles Harris; Jian Tang 005; Jianlin Cheng; Pietro Lio; Tom L. Blundell (ICLR, 2024)

Dynamics-Informed Protein Design with Structure Conditioning. - Urszula Julia Komorowska; Simon V. Mathis; Kieran Didi; Francisco Vargas 001; Pietro Lio; Mateja Jamnik (ICLR, 2024)

How Universal Polynomial Bases Enhance Spectral Graph Neural Networks: Heterophily, Over-smoothing, and Over-squashing. - Keke Huang; Yu Guang Wang 001; Ming Li 065; Pietro Lio (ICML, 2024)

Position: Topological Deep Learning is the New Frontier for Relational Learning. - Theodore Papamarkou; Tolga Birdal; Michael M. Bronstein; Gunnar E. Carlsson; Justin Curry; Yue Gao; Mustafa Hajij; Roland Kwitt; Pietro Lio; Paolo Di Lorenzo; Vasileios Maroulas; Nina Miolane; et al. (ICML, 2024)

Integrating Structure and Sequence: Protein Graph Embeddings via GNNs and LLMs. - Francesco Ceccarelli; Lorenzo Giusti; Sean B. Holden; Pietro Liò (ICPRAM, 2024)

MUGI-MRI: Enhancing Breast Cancer Classification through Multiplex Graph Neural Networks in DCE-MRI. - Francesco Ceccarelli; Francesco Prinzi; Pietro Liò; Salvatore Vitabile; Sean B. Holden (IJCNN, 2024)

Topological Message Passing for Higher - Order and Long - Range Interactions. - Lorenzo Giusti; Teodora Reu; Francesco Ceccarelli; Cristian Bodnar; Pietro Liò (IJCNN, 2024)

xAI-Drop: Don't Use What You Cannot Explain. - Vincenzo Marco De Luca; Antonio Longa; Pietro Lio; Andrea Passerini (LoG, 2024)

TrafficMOT: A Challenging Dataset for Multi-Object Tracking in Complex Traffic Scenarios. - Lihao Liu; Yanqi Cheng; Zhongying Deng; Shujun Wang; Dongdong Chen 001; Xiaowei Hu 001; Pietro Liò; Carola-Bibiane Schönlieb; Angelica E. Avilés-Rivero (ACM Multimedia, 2024)

DEFT: Efficient Fine-tuning of Diffusion Models by Learning the Generalised $h$-transform. - Alexander Denker; Francisco Vargas 001; Shreyas Padhy; Kieran Didi; Simon V. Mathis; Riccardo Barbano; Vincent Dutordoir; Emile Mathieu; Urszula Julia Komorowska; Pietro Lió (NeurIPS, 2024)

Deep Equilibrium Algorithmic Reasoning. - Dobrik Georgiev; Joseph Wilson; Davide Buffelli; Pietro Lió (NeurIPS, 2024)

Optimizing Polynomial Graph Filters: A Novel Adaptive Krylov Subspace Approach. - Keke Huang; Wencai Cao; Hoang Ta 001; Xiaokui Xiao; Pietro Liò (WWW, 2024)

Categorical Foundation of Explainable AI: A Unifying Theory. - Francesco Giannini; Stefano Fioravanti; Pietro Barbiero; Alberto Tonda; Pietro Liò; Elena Di Lavore (xAI (3), 2024)

Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study. - Roksana Akter Raisa; Ayesha Siddika Rodela; Mohammad Abu Yousuf; A. K. M. Azad; Salem A. Alyami; Pietro Liò; Md Zahidul Islam 001; Ganna Pogrebna; Mohammad Ali Moni (IEEE Access, 2024)

The Deep Equilibrium Algorithmic Reasoner. - Dobrik Georgiev; Pietro Liò; Davide Buffelli (CoRR, 2024)

Position Paper: Challenges and Opportunities in Topological Deep Learning. - Theodore Papamarkou; Tolga Birdal; Michael M. Bronstein; Gunnar E. Carlsson; Justin Curry; Yue Gao; Mustafa Hajij; Roland Kwitt; Pietro Liò; Paolo Di Lorenzo; Vasileios Maroulas; Nina Miolane; et al. (CoRR, 2024)

Masked Attention is All You Need for Graphs. - David Buterez; Jon Paul Janet; Dino Oglic; Pietro Lio (CoRR, 2024)

Enhancing Real-World Complex Network Representations with Hyperedge Augmentation. - Xiangyu Zhao; Zehui Li; Mingzhu Shen; Guy-Bart Stan; Pietro Liò; Yiren Zhao (CoRR, 2024)

Understanding Biology in the Age of Artificial Intelligence. - Elsa Lawrence; Adham El-Shazly; Srijit Seal; Chaitanya K. Joshi; Pietro Liò; Shantanu Singh; Andreas Bender 002; Pietro Sormanni; Matthew Greenig (CoRR, 2024)

Leveraging graph neural networks for supporting Automatic Triage of Patients. - Annamaria Defilippo; Pierangelo Veltri; Pietro Lió; Pietro Hiram Guzzi (CoRR, 2024)

Wet TinyML: Chemical Neural Network Using Gene Regulation and Cell Plasticity. - Samitha Somathilaka; Adrian Ratwatte; Sasitharan Balasubramaniam; Mehmet Can Vuran; Witawas Srisa-an; Pietro Liò (CoRR, 2024)

Sphere Neural-Networks for Rational Reasoning. - Tiansi Dong; Mateja Jamnik; Pietro Liò (CoRR, 2024)

DCAE-SR: Design of a Denoising Convolutional Autoencoder for reconstructing Electrocardiograms signals at Super Resolution. - Ugo Lomoio; Pierangelo Veltri; Pietro Hiram Guzzi; Pietro Lio' (CoRR, 2024)

SynFlowNet: Towards Molecule Design with Guaranteed Synthesis Pathways. - Miruna T. Cretu; Charles Harris; Julien Roy; Emmanuel Bengio; Pietro Liò (CoRR, 2024)

Artificial Intelligence-powered fossil shark tooth identification: Unleashing the potential of Convolutional Neural Networks. - Andrea Barucci 001; Giulia Ciacci; Pietro Liò; Tiago Azevedo; Andrea Di Cencio; Marco Merella; Giovanni Bianucci; Giulia Bosio; Simone Casati; Alberto Collareta (CoRR, 2024)

Solving the enigma: Deriving optimal explanations of deep networks. - Michail Mamalakis; Antonios Mamalakis; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Graham K. Murray; John Suckling; Pietro Lio (CoRR, 2024)

Contrastive-Adversarial and Diffusion: Exploring pre-training and fine-tuning strategies for sulcal identification. - Michail Mamalakis; Héloïse de Vareilles; Shun-Chin Jim Wu; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Jane R. Garrison; Jon S. Simons; Pietro Lio; John Suckling; Graham K. Murray (CoRR, 2024)

Sheaf HyperNetworks for Personalized Federated Learning. - Bao Nguyen; Lorenzo Sani; Xinchi Qiu; Pietro Liò; Nicholas D. Lane (CoRR, 2024)

The Explanation Necessity for Healthcare AI. - Michail Mamalakis; Héloïse de Vareilles; Graham K. Murray; Pietro Lio; John Suckling (CoRR, 2024)

DEFT: Efficient Finetuning of Conditional Diffusion Models by Learning the Generalised h-transform. - Alexander Denker; Francisco Vargas 001; Shreyas Padhy; Kieran Didi; Simon V. Mathis; Vincent Dutordoir; Riccardo Barbano; Emile Mathieu; Urszula Julia Komorowska; Pietro Lio (CoRR, 2024)

TabMDA: Tabular Manifold Data Augmentation for Any Classifier using Transformers with In-context Subsetting. - Andrei Margeloiu; Adrián Bazaga; Nikola Simidjievski; Pietro Liò; Mateja Jamnik (CoRR, 2024)

ZeroPur: Succinct Training-Free Adversarial Purification. - Xiuli Bi; Zonglin Yang; Bo Liu 047; Xiaodong Cun; Chi-Man Pun; Pietro Lio; Bin Xiao 002 (CoRR, 2024)

E(n) Equivariant Message Passing Cellular Networks. - Veljko Kovac; Erik J. Bekkers; Pietro Liò; Floor Eijkelboom (CoRR, 2024)

FLUID-LLM: Learning Computational Fluid Dynamics with Spatiotemporal-aware Large Language Models. - Max Zhu; Adrián Bazaga; Pietro Liò (CoRR, 2024)

Improving Antibody Design with Force-Guided Sampling in Diffusion Models. - Paulina Kulyte; Francisco Vargas 001; Simon Valentin Mathis; Yu Guang Wang 001; José Miguel Hernández-Lobato; Pietro Liò (CoRR, 2024)

RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design. - Rishabh Anand; Chaitanya K. Joshi; Alex Morehead; Arian R. Jamasb; Charles Harris; Simon V. Mathis; Kieran Didi; Bryan Hooi; Pietro Liò (CoRR, 2024)

Graph Representation Learning Strategies for Omics Data: A Case Study on Parkinson's Disease. - Elisa Gómez de Lope; Saurabh Deshpande; Ramón Viñas Torné 001; Pietro Liò; Enrico Glaab; Stéphane P. A. Bordas (CoRR, 2024)

G-Adaptive mesh refinement - leveraging graph neural networks and differentiable finite element solvers. - James Rowbottom; Georg Maierhofer; Teo Deveney; Katharina Schratz; Pietro Liò; Carola-Bibiane Schönlieb; Chris J. Budd (CoRR, 2024)

Metric Learning for Clifford Group Equivariant Neural Networks. - Riccardo Ali; Paulina Kulyte; Haitz Sáez de Ocáriz Borde; Pietro Liò (CoRR, 2024)

Joint Diffusion Processes as an Inductive Bias in Sheaf Neural Networks. - Ferran Hernandez Caralt; Guillermo Bernárdez Gil; Iulia Duta; Pietro Liò; Eduard Alarcón-Cot (CoRR, 2024)

GenRec: Generative Personalized Sequential Recommendation. - Panfeng Cao; Pietro Lio (CoRR, 2024)

A Survey for Large Language Models in Biomedicine. - Chong Wang; Mengyao Li; Junjun He; Zhongruo Wang; Erfan Darzi; Zan Chen; Jin Ye 002; Tianbin Li; Yanzhou Su; Jing Ke; Kaili Qu; Shuxin Li; et al. (CoRR, 2024)

Neural Algorithmic Reasoning with Multiple Correct Solutions. - Zeno Kujawa; John Poole; Dobrik Georgiev; Danilo Numeroso; Pietro Liò (CoRR, 2024)

Heterogeneous Sheaf Neural Networks. - Luke Braithwaite; Iulia Duta; Pietro Liò (CoRR, 2024)

Bayesian Binary Search. - Vikash Singh; Matthew Khanzadeh; Vincent Davis; Harrison Rush; Emanuele Rossi; Jesse Shrader; Pietro Lio (CoRR, 2024)

SPHINX: Structural Prediction using Hypergraph Inference Network. - Iulia Duta; Pietro Liò (CoRR, 2024)

Explaining Hypergraph Neural Networks: From Local Explanations to Global Concepts. - Shiye Su; Iulia Duta; Lucie Charlotte Magister; Pietro Liò (CoRR, 2024)

Predicting time-varying flux and balance in metabolic systems using structured neural-ODE processes. - Santanu Rathod; Pietro Lio; Xiao Zhang (CoRR, 2024)

Deep Equilibrium Algorithmic Reasoning. - Dobrik Georgiev; JJ Wilson; Davide Buffelli; Pietro Liò (CoRR, 2024)

Explainable Deep Learning Framework for SERS Bio-quantification. - Jihan K. Zaki; Jakub Tomasik; Jade A. McCune; Sabine Bahn; Pietro Liò; Oren A. Scherman (CoRR, 2024)

Dirac-Equation Signal Processing: Physics Boosts Topological Machine Learning. - Runyue Wang; Yu Tian; Pietro Liò; Ginestra Bianconi (CoRR, 2024)

KG4Diagnosis: A Hierarchical Multi-Agent LLM Framework with Knowledge Graph Enhancement for Medical Diagnosis. - Kaiwen Zuo; Yirui Jiang; Fan Mo; Pietro Lio (CoRR, 2024)

SNDGCN: Robust Android malware detection based on subgraph network and denoising GCN network. - Xiaofeng Lu; Jinglun Zhao; Senhao Zhu; Pietro Lio (Expert Syst. Appl., 2024)

Elegans-AI: How the connectome of a living organism could model artificial neural networks. - Francesco Bardozzo; Andrea Terlizzi; Claudio Simoncini; Pietro Lió; Roberto Tagliaferri (Neurocomputing, 2024)

Adaptive multi-scale Graph Neural Architecture Search framework. - Lintao Yang; Pietro Liò; Xu Shen 002; Yuyang Zhang; Chengbin Peng (Neurocomputing, 2024)

Dual-stream multi-dependency graph neural network enables precise cancer survival analysis. - Zhikang Wang; Jiani Ma; Qian Gao; Chris Bain; Seiya Imoto; Pietro Liò; Hongmin Cai; Hao Chen 011; Jiangning Song (Medical Image Anal., 2024)

Machine learning-aided generative molecular design. - Yuanqi Du; Arian R. Jamasb; Jeff Guo; Tianfan Fu; Charles Harris; Yingheng Wang; Chenru Duan; Pietro Liò; Philippe Schwaller; Tom L. Blundell (Nat. Mac. Intell., 2024)

LandSin: A differential ML and google API-enabled web server for real-time land insights and beyond. - Alauddin Sabari; Imran Hasan; Salem A. Alyami; Pietro Liò; Md. Sadek Ali; Mohammad Ali Moni; A. K. M. Azad (Softw. Impacts, 2024)

GCondNet: A Novel Method for Improving Neural Networks on Small High-Dimensional Tabular Data. - Andrei Margeloiu; Nikola Simidjievski; Pietro Lio; Mateja Jamnik (Trans. Mach. Learn. Res., 2024)

Deep Kernel Learning of Nonlinear Latent Force Models. - Jacob Moss; Jeremy L. England; Pietro Lio (Trans. Mach. Learn. Res., 2024)

Guest Editorial: Deep Neural Networks for Graphs: Theory, Models, Algorithms, and Applications. - Ming Li 065; Alessio Micheli; Yu Guang Wang 001; Shirui Pan; Pietro Lió; Giorgio Stefano Gnecco; Marcello Sanguineti (IEEE Trans. Neural Networks Learn. Syst., 2024)

MISATO: machine learning dataset of protein-ligand complexes for structure-based drug discovery. - Till Siebenmorgen; Filipe Menezes; Sabrina Benassou; Erinc Merdivan; Kieran Didi; André Santos Dias Mourão; Radoslaw Kitel; Pietro Liò; Stefan Kesselheim; Marie Piraud; Fabian J. Theis; Michael Sattler; et al. (Nat. Comput. Sci., 2024)

ASDNet: A robust involution-based architecture for diagnosis of autism spectrum disorder utilising eye-tracking technology. - Nasirul Mumenin; Mohammad Abu Yousuf; Md Asif Nashiry; A. K. M. Azad; Salem A. Alyami; Pietro Lio'; Mohammad Ali Moni (IET Comput. Vis., 2024)

Graph Rewiring and Preprocessing for Graph Neural Networks Based on Effective Resistance. - Xu Shen 002; Pietro Liò; Lintao Yang; Ru Yuan; Yuyang Zhang; Chengbin Peng 001 (IEEE Trans. Knowl. Data Eng., 2024)

Structure-based drug design with equivariant diffusion models. - Arne Schneuing; Charles Harris; Yuanqi Du; Kieran Didi; Arian Rokkum Jamasb; Ilia Igashov; Weitao Du; Carla P. Gomes; Tom L. Blundell; Pietro Lio; Max Welling; Michael M. Bronstein; et al. (Nat. Comput. Sci., 2024)

Neural Reasoning for Sure Through Constructing Explainable Models. - Tiansi Dong; Mateja Jamnik; Pietro Liò (AAAI, 2025)

Deep Hypergraph Neural Networks with Tight Framelets. - Ming Li 065; Yujie Fang; Yi Wang 022; Han Feng; Yongchun Gu; Lu Bai 001; Pietro Liò (AAAI, 2025)

When Hypergraph Meets Heterophily: New Benchmark Datasets and Baseline. - Ming Li 065; Yongchun Gu; Yi Wang 022; Yujie Fang; Lu Bai 001; Xiaosheng Zhuang; Pietro Liò (AAAI, 2025)

Decoding the Stressed Brain with Geometric Machine Learning. - Sonia Koszut; Sam Nallaperuma Herzberg; Pietro Lio (AIiH (2), 2025)

Translating Genes into Insight: Causal Genomics for Diabetes Risk Prediction. - Sheresh Zahoor; Pietro Lió; Gaël Dias; Mohammed Hasanuzzaman (AIiH (1), 2025)

GraphNet: A Novel Method Based on Graph Neural Networks for Emergency Healthcare Management. - Annamaria Defilippo; Pietro Hiram Guzzi; Pierangelo Veltri; Pietro Liò (AIME (2), 2025)

Uncertainty Modeling in Graph Neural Networks via Stochastic Differential Equations. - Richard Bergna; Sergio Calvo-Ordoñez; Felix L. Opolka; Pietro Lio; José Miguel Hernández-Lobato (ICLR, 2025)

SynFlowNet: Design of Diverse and Novel Molecules with Synthesis Constraints. - Miruna T. Cretu; Charles Harris; Ilia Igashov; Arne Schneuing; Marwin H. S. Segler; Bruno E. Correia; Julien Roy; Emmanuel Bengio; Pietro Lio (ICLR, 2025)

gRNAde: Geometric Deep Learning for 3D RNA inverse design. - Chaitanya K. Joshi; Arian Rokkum Jamasb; Ramón Viñas Torné 001; Charles Harris; Simon V. Mathis; Alex Morehead; Rishabh Anand; Pietro Lio (ICLR, 2025)

Advanced Hypergraph Mining for Web Applications Using Sphere Neural Networks. - Zhongtian Sun; Anoushka Harit; Jongmin Yu; Jingyun Wang; Pietro Liò (WWW (Companion Volume), 2025)

Corrections to "Deep and Shallow Learning Model-Based Sleep Apnea Diagnosis Systems: A Comprehensive Study". - Roksana Akter Raisa; Ayesha Siddika Rodela; Mohammad Abu Yousuf; A. K. M. Azad; Salem A. Alyami; Pietro Liò; Md Zahidul Islam 001; Ganna Pogrebna; Mohammad Ali Moni (IEEE Access, 2025)

Solving the enigma: Enhancing faithfulness and comprehensibility in explanations of deep networks. - Michail Mamalakis; Antonios Mamalakis; Ingrid Agartz; Lynn Egeland Mørch-Johnsen; Graham K. Murray; John Suckling; Pietro Lio (AI Open, 2025)

Design and use of a Denoising Convolutional Autoencoder for reconstructing electrocardiogram signals at super resolution. - Ugo Lomoio; Pierangelo Veltri; Pietro Hiram Guzzi; Pietro Liò (Artif. Intell. Medicine, 2025)

Advancing label-free cell classification with connectome-inspired explainable models and a novel LIVECell-CLS dataset. - Pierpaolo Fiore; Andrea Terlizzi; Francesco Bardozzo; Pietro Liò; Roberto Tagliaferri (Comput. Biol. Medicine, 2025)

Artificial Intelligence for Science in Quantum, Atomistic, and Continuum Systems. - Xuan Zhang; Limei Wang; Jacob Helwig; Youzhi Luo; Cong Fu 003; Yaochen Xie; Meng Liu 015; Yuchao Lin; Zhao Xu 005; Keqiang Yan; Keir Adams; Maurice Weiler; et al. (Found. Trends Mach. Learn., 2025)

Self-Simulation and Meta-Model Aggregation-Based Heterogeneous-Graph-Coupled Federated Learning. - Caihong Yan; Xiaofeng Lu; Pietro Lio; Pan Hui 001; Daojing He (IEEE Internet Things J., 2025)

Using AI explainable models and handwriting/drawing tasks for psychological well-being. - Francesco Prinzi; Pietro Barbiero; Claudia Greco; Terry Amorese; Gennaro Cordasco; Pietro Liò; Salvatore Vitabile; Anna Esposito (Inf. Syst., 2025)

EARVP: Efficient Aggregation for Federated Learning With Robustness, Verifiability, and Privacy. - Caihong Yan; Xiaofeng Lu; Pietro Lio; Pan Hui 001 (IEEE Trans. Inf. Forensics Secur., 2025)

A Systematic Review of Heart Sound Detection Algorithms: Experimental Results and Insights. - Xiuli Bi; Shizhan Tang; Bin Xiao 002; Weisheng Li 001; Xinbo Gao 001; Pietro Liò (IEEE Trans. Instrum. Meas., 2025)

RNA-FrameFlow: Flow Matching for de novo 3D RNA Backbone Design. - Rishabh Anand; Chaitanya K. Joshi; Alex Morehead; Arian Rokkum Jamasb; Charles Harris; Simon V. Mathis; Kieran Didi; Rex Ying; Bryan Hooi; Pietro Lio (Trans. Mach. Learn. Res., 2025)

Hypergraph Neural Networks through the Lens of Message Passing: A Common Perspective to Homophily and Architecture Design. - Lev Telyatnikov; Maria Sofia Bucarelli; Guillermo Bernárdez; Olga Zaghen; Simone Scardapane; Pietro Lio (Trans. Mach. Learn. Res., 2025)

Multi-Head Explainer: A General Framework to Improve Explainability in CNNs and Transformers. - Bohang Sun; Pietro Liò (CoRR, 2025)

Integrating Probabilistic Trees and Causal Networks for Clinical and Epidemiological Data. - Sheresh Zahoor; Pietro Liò; Gaël Dias; Mohammed Hasanuzzaman (CoRR, 2025)

Debiasing Guidance for Discrete Diffusion with Sequential Monte Carlo. - Cheuk Kit Lee; Paul Jeha; Jes Frellsen; Pietro Lio; Michael Samuel Albergo; Francisco Vargas 001 (CoRR, 2025)

Towards Mechanistic Interpretability of Graph Transformers via Attention Graphs. - Batu El; Deepro Choudhury; Pietro Liò; Chaitanya K. Joshi (CoRR, 2025)

Entropy-Lens: The Information Signature of Transformer Computations. - Riccardo Ali; Francesco Caso; Christopher Irwin; Pietro Liò (CoRR, 2025)

EU-Nets: Enhanced, Explainable and Parsimonious U-Nets. - Bohang Sun; Pietro Liò (CoRR, 2025)

State of the Art and Potentialities of Graph-level Learning. - Zhenyu Yang 004; Ge Zhang 002; Jia Wu 001; Jian Yang 001; Quan Z. Sheng; Shan Xue 001; Chuan Zhou 001; Charu Aggarwal 001; Hao Peng 001; Wenbin Hu 001; Edwin R. Hancock; Pietro Liò (ACM Comput. Surv., 2025)

Biasing Federated Learning With a New Adversarial Graph Attention Network. - Kai Li 002; Jingjing Zheng; Wei Ni 001; Hailong Huang 001; Pietro Liò; Falko Dressler; Özgür B. Akan (IEEE Trans. Mob. Comput., 2025)

Hierarchical Planning for Complex Tasks with Knowledge Graph-RAG and Symbolic Verification. - Cristina Cornelio; Flavio Petruzzellis; Pietro Lio (CoRR, 2025)

FAIRGAME: a Framework for AI Agents Bias Recognition using Game Theory. - Alessio Buscemi; Daniele Proverbio; Alessandro Di Stefano; The Anh Han; German Castignani; Pietro Liò (CoRR, 2025)

Enhancing Surgical Documentation through Multimodal Visual-Temporal Transformers and Generative AI. - Hugo Georgenthum; Cristian Cosentino; Fabrizio Marozzo; Pietro Liò (CoRR, 2025)

Quantum deep learning in neuroinformatics: a systematic review. - Nabil Anan Orka; Md. Abdul Awal; Pietro Liò; Ganna Pogrebna; Allen G. Ross; Mohammad Ali Moni (Artif. Intell. Rev., 2025)

Sparsity is All You Need: Rethinking Biological Pathway-Informed Approaches in Deep Learning. - Isabella Caranzano; Corrado Pancotti; Cesare Rollo; Flavio Sartori; Pietro Liò; Piero Fariselli; Tiziana Sanavia (CoRR, 2025)

Multi-Level Monte Carlo Training of Neural Operators. - James Rowbottom; Stefania Fresca; Pietro Lio; Carola-Bibiane Schönlieb; Nicolas Boullé (CoRR, 2025)

Graph Foundation Models: A Comprehensive Survey. - Zehong Wang; Zheyuan Liu 010; Tianyi Ma; Jiazheng Li 012; Zheyuan Zhang; Xingbo Fu; Yiyang Li; Zhengqing Yuan; Wei Song; Yijun Ma; Qingkai Zeng 001; Xiusi Chen; et al. (CoRR, 2025)

How Particle System Theory Enhances Hypergraph Message Passing. - Yixuan Ma; Kai Yi; Pietro Lio; Shi Jin; Yu Guang Wang (CoRR, 2025)

Deep Spectral Prior. - Yanqi Cheng; Tieyong Zeng; Pietro Lio; Carola-Bibiane Schönlieb; Angelica I. Avilés-Rivero (CoRR, 2025)

Explaining the Explainers in Graph Neural Networks: a Comparative Study. - Antonio Longa; Steve Azzolin; Gabriele Santin; Giulia Cencetti; Pietro Lio; Bruno Lepri; Andrea Passerini (ACM Comput. Surv., 2025)

Sheaves Reloaded: A Directional Awakening. - Stefano Fiorini; Hakan Aktas; Iulia Duta; Stefano Coniglio; Pietro Morerio; Alessio Del Bue; Pietro Liò (CoRR, 2025)

Parameter-free approximate equivariance for tasks with finite group symmetry. - Riccardo Ali; Pietro Liò; Jamie Vicary (CoRR, 2025)

Wasserstein Hypergraph Neural Network. - Iulia Duta; Pietro Liò (CoRR, 2025)

AutoHFormer: Efficient Hierarchical Autoregressive Transformer for Time Series Prediction. - Qianru Zhang; Honggang Wen; Ming Li 065; Dong Huang 005; Siu-Ming Yiu; Christian S. Jensen; Pietro Liò (CoRR, 2025)

Actionable Interpretability via Causal Hypergraphs: Unravelling Batch Size Effects in Deep Learning. - Zhongtian Sun; Anoushka Harit; Pietro Lio (CoRR, 2025)

TABASCO: A Fast, Simplified Model for Molecular Generation with Improved Physical Quality. - Carlos Vonessen; Charles Harris; Miruna T. Cretu; Pietro Liò (CoRR, 2025)

Uncovering Neuroimaging Biomarkers of Brain Tumor Surgery with AI-Driven Methods. - Carmen Jimenez-Mesa; Yizhou Wan; Guilio Sansone; Francisco Jesús Martínez-Murcia; Javier Ramírez 001; Pietro Lio; Juan Manuel Górriz; Stephen J. Price; John Suckling; Michail Mamalakis (CoRR, 2025)

SynCoGen: Synthesizable 3D Molecule Generation via Joint Reaction and Coordinate Modeling. - Andrei Rekesh; Miruna T. Cretu; Dmytro Shevchuk; Vignesh Ram Somnath; Pietro Liò; Robert A. Batey; Mike Tyers; Michal Koziarski; Cheng-Hao Liu (CoRR, 2025)

GLANCE: Graph Logic Attention Network with Cluster Enhancement for Heterophilous Graph Representation Learning. - Zhongtian Sun; Anoushka Harit; Alexandra I. Cristea; Christl A. Donnelly; Pietro Liò (CoRR, 2025)

Research on Privacy Protection Technology of "2+2" Verifiable Federated Learning. - Pan Wang; Xiaofeng Lu; Pietro Lio (IEEE Internet Things J., 2025)

Strategic Communication and Language Bias in Multi-Agent LLM Coordination. - Alessio Buscemi; Daniele Proverbio; Alessandro Di Stefano; The Anh Han; German Castignani; Pietro Liò (CoRR, 2025)

Multimodal Attention-Aware Fusion for Diagnosing Distal Myopathy: Evaluating Model Interpretability and Clinician Trust. - Mohsen Abbaspour Onari; Lucie Charlotte Magister; Yaoxin Wu; Amalia Lupi; Dario Creazzo; Mattia Tordin; Luigi Di Donatantonio; Emilio Quaia; Chao Zhang 071; Isel Grau; Marco S. Nobile; Yingqian Zhang 001; et al. (CoRR, 2025)

Stochastic Encodings for Active Feature Acquisition. - Alexander Norcliffe; Changhee Lee; Fergus Imrie; Mihaela van der Schaar; Pietro Lio (CoRR, 2025)

Can LLMs effectively provide game-theoretic-based scenarios for cybersecurity? - Daniele Proverbio; Alessio Buscemi; Alessandro Di Stefano; The Anh Han; German Castignani; Pietro Liò (CoRR, 2025)

HealthBranches: Synthesizing Clinically-Grounded Question Answering Datasets via Decision Pathways. - Cristian Cosentino; Annamaria Defilippo; Marco Dossena; Christopher Irwin; Sara Joubbi; Pietro Liò (CoRR, 2025)

Survey on Leveraging Uncertainty Estimation Towards Trustworthy Deep Neural Networks: The Case of Reject Option and Post-training Processing. - Md Mehedi Hasan; Moloud Abdar; Abbas Khosravi; Uwe Aickelin; Pietro Lio; Ibrahim Hossain; Ashikur Rahman; Saeid Nahavandi (ACM Comput. Surv., 2025)