Bi-Causal Recurrent Cascade Correlation. - Alessio Micheli; Diego Sona; Alessandro Sperduti (IJCNN (3), 2000)

Building MLP Networks by Construction. - Ah Chung Tsoi; Markus Hagenbuchner; Alessio Micheli (IJCNN (4), 2000)

Application of Cascade Correlation Networks for Structures to Chemistry. - Anna Maria Bianucci; Alessio Micheli; Alessandro Sperduti; Antonina Starita (Appl. Intell., 2000)

Analysis of the Internal Representations Developed by Neural Networks for Structures Applied to Quantitative Structure-Activity Relationship Studies of Benzodiazepines. - Alessio Micheli; Alessandro Sperduti; Antonina Starita; Anna Maria Bianucci (J. Chem. Inf. Comput. Sci., 2001)

A general framework for unsupervised processing of structured data. - Barbara Hammer; Alessio Micheli; Alessandro Sperduti (ESANN, 2002)

Formal Determination of Context in Contextual Recursive Cascade Correlation Networks. - Alessio Micheli; Diego Sona; Alessandro Sperduti (ICANN, 2003)

QSAR/QSPR Studies by Kernel Machines, Recursive Neural Networks and Their Integration. - Alessio Micheli; Filippo Portera; Alessandro Sperduti (WIRN, 2003)

A preliminary experimental comparison of recursive neural networks and a tree kernel method for QSAR/QSPR regression tasks. - Alessio Micheli; Filippo Portera; Alessandro Sperduti (ESANN, 2004)

Fisher kernel for tree structured data. - Luca Nicotra; Alessio Micheli; Antonina Starita (IJCNN, 2004)

A Preliminary Investigation on Connecting Genotype to Oral Cancer Development through XCS. - Flavio Baronti; Valentina Maggini; Alessio Micheli; Alessandro Passaro; Anna Maria Rossi; Antonina Starita (WIRN, 2004)

A general framework for unsupervised processing of structured data. - Barbara Hammer; Alessio Micheli; Alessandro Sperduti; Marc Strickert (Neurocomputing, 2004)

Recursive self-organizing network models. - Barbara Hammer; Alessio Micheli; Alessandro Sperduti; Marc Strickert (Neural Networks, 2004)

Contextual processing of structured data by recursive cascade correlation. - Alessio Micheli; Diego Sona; Alessandro Sperduti (IEEE Trans. Neural Networks, 2004)

A New Neural Network Model for Contextual Processing of Graphs. - Alessio Micheli; Antonio S. Sestito (WIRN/NAIS, 2005)

A preliminary empirical comparison of recursive neural networks and tree kernel methods on regression tasks for tree structured domains. - Alessio Micheli; Filippo Portera; Alessandro Sperduti (Neurocomputing, 2005)

Universal Approximation Capability of Cascade Correlation for Structures. - Barbara Hammer; Alessio Micheli; Alessandro Sperduti (Neural Comput., 2005)

Predicting Physical-Chemical Properties of Compounds from Molecular Structures by Recursive Neural Networks. - Luca Bernazzani; Celia Duce; Alessio Micheli; Vincenzo Mollica; Alessandro Sperduti; Antonina Starita; Maria Rosaria Tiné (J. Chem. Inf. Model., 2006)

A general framework for unsupervised preocessing of structured data. - Barbara Hammer; Alessio Micheli; Alessandro Sperduti (Probabilistic, Logical and Relational Learning - A Further Synthesis, 2007)

Recursive Principal Component Analysis of Graphs. - Alessio Micheli; Alessandro Sperduti (ICANN (2), 2007)

Generative Kernels for Gene Function Prediction Through Probabilistic Tree Models of Evolution. - Luca Nicotra; Alessio Micheli; Antonina Starita (WILF, 2007)

Adaptive Contextual Processing of Structured Data by Recursive Neural Networks: A Survey of Computational Properties. - Barbara Hammer; Alessio Micheli; Alessandro Sperduti (Perspectives of Neural-Symbolic Integration, 2007)

Modeling adaptive kernels from probabilistic phylogenetic trees. - Luca Nicotra; Alessio Micheli (Artif. Intell. Medicine, 2009)

Neural Network for Graphs: A Contextual Constructive Approach. - Alessio Micheli (IEEE Trans. Neural Networks, 2009)

Recursive Neural Networks for Cheminformatics: QSPR for Polymeric Compounds (Towards Biomaterials Design). - Alessio Micheli; Carlo Bertinetto; Celia Duce; Roberto Solaro; Maria Rosaria Tiné (Computational Intelligence and Bioengineering, 2009)

A Markovian characterization of redundancy in echo state networks by PCA. - Claudio Gallicchio; Alessio Micheli (ESANN, 2010)

TreeESN: a Preliminary Experimental Analysis. - Claudio Gallicchio; Alessio Micheli (ESANN, 2010)

Bottom-Up Generative Modeling of Tree-Structured Data. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (ICONIP (1), 2010)

Compositional generative mapping of structured data. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (IJCNN, 2010)

Graph Echo State Networks. - Claudio Gallicchio; Alessio Micheli (IJCNN, 2010)

Exploiting vertices states in GraphESN by weighted nearest neighbor. - Claudio Gallicchio; Alessio Micheli (ESANN, 2011)

Adaptive tree kernel by multinomial generative topographic mapping. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (IJCNN, 2011)

User Movements Forecasting by Reservoir Computing Using Signal Streams Produced by Mote-Class Sensors. - Claudio Gallicchio; Alessio Micheli; Paolo Barsocchi; Stefano Chessa (MOBILIGHT, 2011)

Supervised State Mapping of Clustered GraphESN States. - Claudio Gallicchio; Alessio Micheli (WIRN, 2011)

Architectural and Markovian factors of echo state networks. - Claudio Gallicchio; Alessio Micheli (Neural Networks, 2011)

Input-Output Hidden Markov Models for trees. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (ESANN, 2012)

Constructive Reservoir Computation with Output Feedbacks for Structured Domains. - Claudio Gallicchio; Alessio Micheli; Giulio Visco (ESANN, 2012)

A Generative Multiset Kernel for Structured Data. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (ICANN (1), 2012)

Robotic UBIquitous COgnitive Network. - Giuseppe Amato 001; Mathias Broxvall; Stefano Chessa; Mauro Dragone; Claudio Gennaro; Rafa López; Liam P. Maguire; T. Martin McGinnity; Alessio Micheli; Arantxa Rentería; Gregory M. P. O'Hare; Federico Pecora (ISAmI, 2012)

A General Purpose Distributed Learning Model for Robotic Ecologies. - Davide Bacciu; Stefano Chessa; Claudio Gallicchio; Alessandro Lenzi; Alessio Micheli; Susanna Pelagatti (SyRoCo, 2012)

An Experimental Evaluation of Reservoir Computation for Ambient Assisted Living. - Davide Bacciu; Stefano Chessa; Claudio Gallicchio; Alessio Micheli; Paolo Barsocchi (WIRN, 2012)

Compositional Generative Mapping for Tree-Structured Data - Part I: Bottom-Up Probabilistic Modeling of Trees. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (IEEE Trans. Neural Networks Learn. Syst., 2012)

Multisensor Data Fusion for Activity Recognition Based on Reservoir Computing. - Filippo Palumbo; Paolo Barsocchi; Claudio Gallicchio; Stefano Chessa; Alessio Micheli (EvAAL, 2013)

Distributed Neural Computation over WSN in Ambient Intelligence. - Davide Bacciu; Claudio Gallicchio; Alessandro Lenzi; Stefano Chessa; Alessio Micheli; Susanna Pelagatti; Claudio Vairo (ISAmI, 2013)

Robot Localization by Echo State Networks Using RSS. - Stefano Chessa; Claudio Gallicchio; Roberto Guzmán; Alessio Micheli (WIRN, 2013)

Italian Machine Learning and Data Mining research: The last years. - Nicola Di Mauro; Paolo Frasconi; Fabrizio Angiulli; Davide Bacciu; Marco de Gemmis; Floriana Esposito; Nicola Fanizzi; Stefano Ferilli; Marco Gori; Francesca A. Lisi; Pasquale Lops; Donato Malerba; et al. (Intelligenza Artificiale, 2013)

Forecast-Driven Enhancement of Received Signal Strength (RSS)-Based Localization Systems. - Paolo Barsocchi; Stefano Chessa; Alessio Micheli; Claudio Gallicchio (ISPRS Int. J. Geo Inf., 2013)

An input-output hidden Markov model for tree transductions. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (Neurocomputing, 2013)

Tree Echo State Networks. - Claudio Gallicchio; Alessio Micheli (Neurocomputing, 2013)

Novel approaches in machine learning and computational intelligence. - Alessio Micheli; Frank-Michael Schleif; Peter Tiño (Neurocomputing, 2013)

Compositional Generative Mapping for Tree-Structured Data - Part II: Topographic Projection Model. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (IEEE Trans. Neural Networks Learn. Syst., 2013)

Modeling Bi-directional Tree Contexts by Generative Transductions. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (ICONIP (1), 2014)

Learning context-aware mobile robot navigation in home environments. - Davide Bacciu; Claudio Gallicchio; Alessio Micheli; Maurizio Di Rocco; Alessandro Saffiotti (IISA, 2014)

Integrating bi-directional contexts in a generative kernel for trees. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (IJCNN, 2014)

An experimental characterization of reservoir computing in ambient assisted living applications. - Davide Bacciu; Paolo Barsocchi; Stefano Chessa; Claudio Gallicchio; Alessio Micheli (Neural Comput. Appl., 2014)

Smart Environments and Context-Awareness for Lifestyle Management in a Healthy Active Ageing Framework. - Davide Bacciu; Stefano Chessa; Claudio Gallicchio; Alessio Micheli; Erina Ferro; Luigi Fortunati; Filippo Palumbo; Oberdan Parodi; Federico Vozzi; Sten Hanke; Johannes Kropf; Karl Kreiner (EPIA, 2015)

ESNigma: efficient feature selection for echo state networks. - Davide Bacciu; Filippo Benedetti; Alessio Micheli (ESANN, 2015)

Structured parallel implementation of Tree Echo State Network model selection. - Marco Danelutto; Claudio Gallicchio; Alessio Micheli; Massimo Torquati; Daniele Virgilio (PARCO, 2015)

A Reservoir Computing Approach for Balance Assessment. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli; Luigi Fortunati; Federico Vozzi; Oberdan Parodi (AALTD@PKDD/ECML (Revised Selected Papers), 2015)

Preliminary Experimental Analysis of Reservoir Computing Approach for Balance Assessment. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli; Federico Vozzi; Oberdan Parodi (AALTD@PKDD/ECML, 2015)

A cognitive robotic ecology approach to self-configuring and evolving AAL systems. - Mauro Dragone; Giuseppe Amato 001; Davide Bacciu; Stefano Chessa; Sonya A. Coleman; Maurizio Di Rocco; Claudio Gallicchio; Claudio Gennaro; Héctor Lozano Peiteado; Liam P. Maguire; T. Martin McGinnity; Alessio Micheli; et al. (Eng. Appl. Artif. Intell., 2015)

Prediction of the Italian electricity price for smart grid applications. - Emanuele Crisostomi; Claudio Gallicchio; Alessio Micheli; Marco Raugi; Mauro Tucci (Neurocomputing, 2015)

Robotic Ubiquitous Cognitive Ecology for Smart Homes. - Giuseppe Amato 001; Davide Bacciu; Mathias Broxvall; Stefano Chessa; Sonya A. Coleman; Maurizio Di Rocco; Mauro Dragone; Claudio Gallicchio; Claudio Gennaro; Héctor Lozano Peiteado; T. Martin McGinnity; Alessio Micheli; et al. (J. Intell. Robotic Syst., 2015)

A Reservoir Computing Approach for Human Gesture Recognition from Kinect Data. - Claudio Gallicchio; Alessio Micheli (AI*AAL@AI*IA, 2016)

A reservoir activation kernel for trees. - Davide Bacciu; Claudio Gallicchio; Alessio Micheli (ESANN, 2016)

RSS-based Robot Localization in Critical Environments using Reservoir Computing. - Mauro Dragone; Claudio Gallicchio; Roberto Guzmán; Alessio Micheli (ESANN, 2016)

Deep Reservoir Computing: A Critical Analysis. - Claudio Gallicchio; Alessio Micheli (ESANN, 2016)

Detecting Socialization Events in Ageing People: The Experience of the DOREMI Project. - Davide Bacciu; Stefano Chessa; Erina Ferro; Luigi Fortunati; Claudio Gallicchio; Davide La Rosa; Miguel Llorente; Alessio Micheli; Filippo Palumbo; Oberdan Parodi; Andrea Valenti; Federico Vozzi (Intelligent Environments, 2016)

A Benchmark Dataset for Human Activity Recognition and Ambient Assisted Living. - Giuseppe Amato 001; Davide Bacciu; Stefano Chessa; Mauro Dragone; Claudio Gallicchio; Claudio Gennaro; Héctor Lozano Peiteado; Alessio Micheli; Gregory M. P. O'Hare; Arantxa Rentería; Claudio Vairo (ISAmI, 2016)

Human activity recognition using multisensor data fusion based on Reservoir Computing. - Filippo Palumbo; Claudio Gallicchio; Rita Pucci; Alessio Micheli (J. Ambient Intell. Smart Environ., 2016)

Indoor User Movement Prediction from RSS data. - Davide Bacciu; Paolo Barsocchi; Stefano Chessa; Claudio Gallicchio; Alessio Micheli (UCI Machine Learning Repository, 2016)

Activity Recognition system based on Multisensor data fusion (AReM). - Filippo Palumbo; Claudio Gallicchio; Rita Pucci; Alessio Micheli (UCI Machine Learning Repository, 2016)

Experimental Analysis of Deep Echo State Networks for Ambient Assisted Living. - Claudio Gallicchio; Alessio Micheli (AI*AAL@AI*IA, 2017)

Randomized Machine Learning Approaches: Recent Developments and Challenges. - Claudio Gallicchio; José David Martín-Guerrero; Alessio Micheli; Emilio Soria-Olivas (ESANN, 2017)

Local Lyapunov Exponents of Deep RNN. - Claudio Gallicchio; Alessio Micheli; Luca Silvestri (ESANN, 2017)

On the need of machine learning as a service for the internet of things. - Davide Bacciu; Stefano Chessa; Claudio Gallicchio; Alessio Micheli (IML, 2017)

A Comparative Analysis of SVM and IDNN for Identifying Penguin Activities. - Stefano Chessa; Alessio Micheli; Rita Pucci; Jane Hunter 001; Gemma Carroll; Rob Harcourt (Appl. Artif. Intell., 2017)

Echo State Property of Deep Reservoir Computing Networks. - Claudio Gallicchio; Alessio Micheli (Cogn. Comput., 2017)

Hierarchical Temporal Representation in Linear Reservoir Computing. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli (CoRR, 2017)

Deep Echo State Network (DeepESN): A Brief Survey. - Claudio Gallicchio; Alessio Micheli (CoRR, 2017)

A learning system for automatic Berg Balance Scale score estimation. - Davide Bacciu; Stefano Chessa; Claudio Gallicchio; Alessio Micheli; Luca Pedrelli; Erina Ferro; Luigi Fortunati; Davide La Rosa; Filippo Palumbo; Federico Vozzi; Oberdan Parodi (Eng. Appl. Artif. Intell., 2017)

Deep reservoir computing: A critical experimental analysis. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli (Neurocomputing, 2017)

Reliability and human factors in Ambient Assisted Living environments - The DOREMI case study. - Filippo Palumbo; Davide La Rosa; Erina Ferro; Davide Bacciu; Claudio Gallicchio; Alessio Micheli; Stefano Chessa; Federico Vozzi; Oberdan Parodi (J. Reliab. Intell. Environ., 2017)

Deep Echo State Networks for Diagnosis of Parkinson's Disease. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli (ESANN, 2018)

Randomized Recurrent Neural Networks. - Claudio Gallicchio; Alessio Micheli; Peter Tiño (ESANN, 2018)

ITAmoji 2018: Emoji Prediction via Tree Echo State Networks. - Daniele Di Sarli; Claudio Gallicchio; Alessio Micheli (EVALITA@CLiC-it, 2018)

Combining Memory and Non-linearity in Echo State Networks. - Eleonora Di Gregorio; Claudio Gallicchio; Alessio Micheli (ICANN (2), 2018)

Contextual Graph Markov Model: A Deep and Generative Approach to Graph Processing. - Davide Bacciu; Federico Errica; Alessio Micheli (ICML, 2018)

Tree Edit Distance Learning via Adaptive Symbol Embeddings. - Benjamin Paaßen; Claudio Gallicchio; Alessio Micheli; Barbara Hammer (ICML, 2018)

Why Layering in Recurrent Neural Networks? A DeepESN Survey. - Claudio Gallicchio; Alessio Micheli (IJCNN, 2018)

Deep Tree Echo State Networks. - Claudio Gallicchio; Alessio Micheli (IJCNN, 2018)

Local Lyapunov exponents of deep echo state networks. - Claudio Gallicchio; Alessio Micheli; Luca Silvestri (Neurocomputing, 2018)

Design of deep echo state networks. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli (Neural Networks, 2018)

Generative Kernels for Tree-Structured Data. - Davide Bacciu; Alessio Micheli; Alessandro Sperduti (IEEE Trans. Neural Networks Learn. Syst., 2018)

Question Classification with Untrained Recurrent Embeddings. - Daniele Di Sarli; Claudio Gallicchio; Alessio Micheli (AI*IA, 2019)

Graph generation by sequential edge prediction. - Davide Bacciu; Alessio Micheli; Marco Podda (ESANN, 2019)

Comparison between DeepESNs and gated RNNs on multivariate time-series prediction. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli (ESANN, 2019)

Embeddings and Representation Learning for Structured Data. - Benjamin Paaßen; Claudio Gallicchio; Alessio Micheli; Alessandro Sperduti (ESANN, 2019)

Continuous Blood Pressure Estimation Through Optimized Echo State Networks. - Giuseppe Franco; Luca Cerina; Claudio Gallicchio; Alessio Micheli; Marco Domenico Santambrogio (ICANN (Workshop), 2019)

Reservoir Topology in Deep Echo State Networks. - Claudio Gallicchio; Alessio Micheli (ICANN (Workshop), 2019)

Deep Learning for Graphs. - Davide Bacciu; Alessio Micheli (INNSBDDL (Tutorials), 2019)

Fast Spectral Radius Initialization for Recurrent Neural Networks. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli (INNSBDDL, 2019)

Richness of Deep Echo State Network Dynamics. - Claudio Gallicchio; Alessio Micheli (IWANN (1), 2019)

An ambient intelligence approach for learning in smart robotic environments. - Davide Bacciu; Maurizio Di Rocco; Mauro Dragone; Claudio Gallicchio; Alessio Micheli; Alessandro Saffiotti (Comput. Intell., 2019)

Deep Reservoir Neural Networks for Trees. - Claudio Gallicchio; Alessio Micheli (Inf. Sci., 2019)

Editorial: Booming of Neural Networks and Learning Systems. - Akira Hirose 001; Alessio Micheli; Artur S. d'Avila Garcez; Choon Ki Ahn; Gang Pan 001; Hamid Reza Karimi; Jianbing Shen; José de Jesús Rubio; Lei Zhang 005; Lingjia Liu 001; Lorenzo Livi; Nian Zhang; et al. (IEEE Trans. Neural Networks Learn. Syst., 2019)

Fast and Deep Graph Neural Networks. - Claudio Gallicchio; Alessio Micheli (AAAI, 2020)

A Deep Generative Model for Fragment-Based Molecule Generation. - Marco Podda; Davide Bacciu; Alessio Micheli (AISTATS, 2020)

Prediction of Dynamical Properties of Biochemical Pathways with Graph Neural Networks. - Pasquale Bove; Alessio Micheli; Paolo Milazzo; Marco Podda (BIOINFORMATICS, 2020)

Classification of Biochemical Pathway Robustness with Neural Networks for Graphs. - Marco Podda; Pasquale Bove; Alessio Micheli; Paolo Milazzo (BIOSTEC (Selected Papers), 2020)

Efficient Embedded Machine Learning applications using Echo State Networks. - Luca Cerina; Marco D. Santambrogio; Giuseppe Franco; Claudio Gallicchio; Alessio Micheli (DATE, 2020)

Pyramidal Graph Echo State Networks. - Filippo Maria Bianchi; Claudio Gallicchio; Alessio Micheli (ESANN, 2020)

Theoretically Expressive and Edge-aware Graph Learning. - Federico Errica; Davide Bacciu; Alessio Micheli (ESANN, 2020)

Simplifying Deep Reservoir Architectures. - Claudio Gallicchio; Alessio Micheli; Antonio Sisbarra (ESANN, 2020)

Biochemical Pathway Robustness Prediction with Graph Neural Networks. - Marco Podda; Alessio Micheli; Davide Bacciu; Paolo Milazzo (ESANN, 2020)

Time Series Clustering with Deep Reservoir Computing. - Miguel A. Atencia Ruiz; Claudio Gallicchio; Gonzalo Joya; Alessio Micheli (ICANN (2), 2020)

A Preliminary Investigation of Machine Learning Approaches for Mobility Monitoring from Smartphone Data. - Claudio Gallicchio; Alessio Micheli; Massimiliano Petri; Antonio Pratelli (ICCSA (2), 2020)

A Fair Comparison of Graph Neural Networks for Graph Classification. - Federico Errica; Marco Podda; Davide Bacciu; Alessio Micheli (ICLR, 2020)

Ring Reservoir Neural Networks for Graphs. - Claudio Gallicchio; Alessio Micheli (IJCNN, 2020)

Gated Echo State Networks: a preliminary study. - Daniele Di Sarli; Claudio Gallicchio; Alessio Micheli (INISTA, 2020)

Machine learning approaches for identifying prey handling activity in otariid pinnipeds. - Rita Pucci; Alessio Micheli; Stefano Chessa; Jane Hunter 001 (CoRR, 2020)

Accelerating the identification of informative reduced representations of proteins with deep learning for graphs. - Federico Errica; Marco Giulini; Davide Bacciu; Roberto Menichetti; Alessio Micheli; Raffaello Potestio (CoRR, 2020)

Text classification by untrained sentence embeddings. - Daniele Di Sarli; Claudio Gallicchio; Alessio Micheli (Intelligenza Artificiale, 2020)

Edge-based sequential graph generation with recurrent neural networks. - Davide Bacciu; Alessio Micheli; Marco Podda (Neurocomputing, 2020)

Probabilistic Learning on Graphs via Contextual Architectures. - Davide Bacciu; Federico Errica; Alessio Micheli (J. Mach. Learn. Res., 2020)

A gentle introduction to deep learning for graphs. - Davide Bacciu; Federico Errica; Alessio Micheli; Marco Podda (Neural Networks, 2020)

EchoBay: Design and Optimization of Echo State Networks under Memory and Time Constraints. - Luca Cerina; Marco D. Santambrogio; Giuseppe Franco; Claudio Gallicchio; Alessio Micheli (ACM Trans. Archit. Code Optim., 2020)

Hierarchical Temporal Representation in Linear Reservoir Computing. - Claudio Gallicchio; Alessio Micheli; Luca Pedrelli (Neural Advances in Processing Nonlinear Dynamic Signals, 2020)

TEACHING - Trustworthy autonomous cyber-physical applications through human-centred intelligence. - Davide Bacciu; Siranush Akarmazyan; Eric Armengaud; Manlio Bacco; George Bravos; Calogero Calandra; Emanuele Carlini; Antonio Carta; Pietro Cassarà; Massimo Coppola; Charalampos Davalas; Patrizio Dazzi; et al. (COINS, 2021)

Robust Malware Classification via Deep Graph Networks on Call Graph Topologies. - Federico Errica; Giacomo Iadarola; Fabio Martinelli; Francesco Mercaldo; Alessio Micheli (ESANN, 2021)

Complex Data: Learning Trustworthily, Automatically, and with Guarantees. - Luca Oneto; Nicolò Navarin; Battista Biggio; Federico Errica; Alessio Micheli; Franco Scarselli; Monica Bianchini; Alessandro Sperduti (ESANN, 2021)

Dynamic Graph Echo State Networks. - Domenico Tortorella; Alessio Micheli (ESANN, 2021)

Graph Mixture Density Networks. - Federico Errica; Davide Bacciu; Alessio Micheli (ICML, 2021)

Modeling Edge Features with Deep Bayesian Graph Networks. - Daniele Atzeni; Davide Bacciu; Federico Errica; Alessio Micheli (IJCNN, 2021)

Federated Reservoir Computing Neural Networks. - Davide Bacciu; Daniele Di Sarli; Pouria Faraji; Claudio Gallicchio; Alessio Micheli (IJCNN, 2021)

Phase Transition Adaptation. - Claudio Gallicchio; Alessio Micheli; Luca Silvestri (IJCNN, 2021)

Benchmarking Reservoir and Recurrent Neural Networks for Human State and Activity Recognition. - Davide Bacciu; Daniele Di Sarli; Claudio Gallicchio; Alessio Micheli; Niccolò Puccinelli (IWANN (2), 2021)

A preliminary evaluation of Echo State Networks for Brugada syndrome classification. - Giovanna Maria Dimitri; Claudio Gallicchio; Alessio Micheli; Maria-Aurora Morales; Emanuele Ungaro; Federico Vozzi (SSCI, 2021)

Deep Reservoir Computing. - Claudio Gallicchio; Alessio Micheli (Reservoir Computing, 2021)

Input Routed Echo State Networks. - Luca Argentieri; Claudio Gallicchio; Alessio Micheli (ESANN, 2022)

Beyond Homophily with Graph Echo State Networks. - Domenico Tortorella; Alessio Micheli (ESANN, 2022)

Hierarchical Dynamics in Deep Echo State Networks. - Domenico Tortorella; Claudio Gallicchio; Alessio Micheli (ICANN (3), 2022)

The Infinite Contextual Graph Markov Model. - Daniele Castellana; Federico Errica; Davide Bacciu; Alessio Micheli (ICML, 2022)

Spectral Bounds for Graph Echo State Network Stability. - Domenico Tortorella; Claudio Gallicchio; Alessio Micheli (IJCNN, 2022)

On the effectiveness of Gated Echo State Networks for data exhibiting long-term dependencies. - Daniele Di Sarli; Claudio Gallicchio; Alessio Micheli (Comput. Sci. Inf. Syst., 2022)

Leave Graphs Alone: Addressing Over-Squashing without Rewiring. - Domenico Tortorella; Alessio Micheli (CoRR, 2022)

Pyramidal Reservoir Graph Neural Network. - Filippo Maria Bianchi; Claudio Gallicchio; Alessio Micheli (Neurocomputing, 2022)

Discrete-time dynamic graph echo state networks. - Alessio Micheli; Domenico Tortorella (Neurocomputing, 2022)

Towards learning trustworthily, automatically, and with guarantees on graphs: An overview. - Luca Oneto; Nicolò Navarin; Battista Biggio; Federico Errica; Alessio Micheli; Franco Scarselli; Monica Bianchini; Luca Demetrio; Pietro Bongini; Armando Tacchella; Alessandro Sperduti (Neurocomputing, 2022)

Guest Editorial Special Issue on New Frontiers in Extremely Efficient Reservoir Computing. - Gouhei Tanaka; Claudio Gallicchio; Alessio Micheli; Juan-Pablo Ortega; Akira Hirose 001 (IEEE Trans. Neural Networks Learn. Syst., 2022)

Pre-trained Models Based on Primary Sequence to Classify Antibody Binding to Protein and Non-protein Targets with 80% Accuracy. - Sara Joubbi; Giuseppe Maccari; Dario Cardamone; Giorgio Ciano; Alessio Micheli; Paolo Milazzo; Duccio Medini (CIBB, 2023)

Graph Representation Learning. - Davide Bacciu; Federico Errica; Alessio Micheli; Nicolò Navarin; Luca Pasa; Marco Podda; Daniele Zambon (ESANN, 2023)

Hidden Markov Models for Temporal Graph Representation Learning. - Federico Errica; Alessio Gravina; Davide Bacciu; Alessio Micheli (ESANN, 2023)

Entropy Based Regularization Improves Performance in the Forward-Forward Algorithm. - Matteo Pardi; Domenico Tortorella; Alessio Micheli (ESANN, 2023)

Richness of Node Embeddings in Graph Echo State Networks. - Domenico Tortorella; Alessio Micheli (ESANN, 2023)

Minimum Spanning Set Selection in Graph Kernels. - Domenico Tortorella; Alessio Micheli (GbRPR, 2023)

Analysis and Interpretation of ECG Time Series Through Convolutional Neural Networks in Brugada Syndrome Diagnosis. - Alessio Micheli; Marco Natali; Luca Pedrelli; Lorenzo Simone; Maria-Aurora Morales; Marcello Piacenti; Federico Vozzi (ICANN (4), 2023)

A Preliminary Evaluation of Machine Learning Models for the Diagnosis of Brugada Syndrome from ECG-Extracted Features. - Alessio Micheli; Giovanna Maria Dimitri; Luca Pedrelli; Marco Tranchida; Lorenzo Bachi; Lucia Billeci; Maria-Aurora Morales; Federico Vozzi (WIRN, 2023)

Is Rewiring Actually Helpful in Graph Neural Networks? - Domenico Tortorella; Alessio Micheli (CoRR, 2023)

Addressing heterophily in node classification with graph echo state networks. - Alessio Micheli; Domenico Tortorella (Neurocomputing, 2023)

Biochemical networks with simulation-based estimations of dynamical properties. - Michele Fontanesi; Paolo Milazzo; Alessio Micheli; Marco Podda (Zenodo, 2023)

Guest Editorial: Trends in Reservoir Computing. - Simone Scardapane; Claudio Gallicchio; Alessio Micheli; Miguel C. Soriano (Cogn. Comput., 2023)

PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs. - Federico Errica; Davide Bacciu; Alessio Micheli (Zenodo, 2023)

Exploiting the structure of biochemical pathways to investigate dynamical properties with neural networks for graphs. - Michele Fontanesi; Alessio Micheli; Paolo Milazzo; Marco Podda (Bioinform., 2023)

PyDGN: a Python Library for Flexible and Reproducible Research on Deep Learning for Graphs. - Federico Errica; Davide Bacciu; Alessio Micheli (J. Open Source Softw., 2023)

Architectural richness in deep reservoir computing. - Claudio Gallicchio; Alessio Micheli (Neural Comput. Appl., 2023)

Relating Explanations with the Inductive Biases of Deep Graph Networks. - Michele Fontanesi; Alessio Micheli; Marco Podda (AI*IA, 2024)

Exposing Inductive Biases of Deep Graph Networks through Explainable AI (Short paper). - Michele Fontanesi; Alessio Micheli; Marco Podda (DC@AI*IA, 2024)

Analyzing Explanations of Deep Graph Networks Through Node Centrality and Connectivity. - Michele Fontanesi; Alessio Micheli; Marco Podda; Domenico Tortorella (DS (1), 2024)

XAI and Bias of Deep Graph Networks. - Michele Fontanesi; Alessio Micheli; Marco Podda (ESANN, 2024)

Informed Machine Learning for Complex Data. - Luca Oneto; Nicolò Navarin; Alessio Micheli; Luca Pasa; Claudio Gallicchio; Davide Bacciu; Davide Anguita (ESANN, 2024)

Continual Learning with Graph Reservoirs: Preliminary experiments in graph classification. - Domenico Tortorella; Alessio Micheli (ESANN, 2024)

Hybrid CNN-MLP for Wastewater Quality Estimation. - Marco Cardia; Stefano Chessa; Alessio Micheli; Antonella Giuliana Luminare; Francesca Gambineri (ICANN (9), 2024)

Onion Echo State Networks - A Preliminary Analysis of Dynamics. - Domenico Tortorella; Alessio Micheli (ICANN (10), 2024)

Multitarget Wastewater Quality Assessment in a Smart Industry Context. - Marco Cardia; Stefano Chessa; Alessio Micheli; Antonella Giuliana Luminare; Massimiliano Franceschi; Francesca Gambineri (IE, 2024)

Machine Learning Approach for Labeling Undetected Planned Trips in Public Transport Operators. - Mohammad Amin Zadenoori; Marco Calamai; Francesca Del Lungo; Daria Faucci; Andrea Gaffi; Lorenzo Sarti; Alessio Micheli (INTSYS, 2024)

Continuously Deep Recurrent Neural Networks. - Andrea Ceni; Peter Ford Dominey; Claudio Gallicchio; Alessio Micheli; Luca Pedrelli; Domenico Tortorella (ECML/PKDD (7), 2024)

Wastewater Quality Indicator Estimation Using Machine Learning and Data Augmentation Techniques. - Marco Cardia; Stefano Chessa; Alessio Micheli; Antonella Giuliana Luminare; Francesca Gambineri (SOCO (1), 2024)

Explaining Graph Classifiers by Unsupervised Node Relevance Attribution. - Michele Fontanesi; Alessio Micheli; Marco Podda (xAI (2), 2024)

Antibody design using deep learning: from sequence and structure design to affinity maturation. - Sara Joubbi; Alessio Micheli; Paolo Milazzo; Giuseppe Maccari; Giorgio Ciano; Dario Cardamone; Duccio Medini (Briefings Bioinform., 2024)

Investigating over-parameterized randomized graph networks. - Giovanni Donghi; Luca Pasa; Luca Oneto; Claudio Gallicchio; Alessio Micheli; Davide Anguita; Alessandro Sperduti; Nicolò Navarin (Neurocomputing, 2024)

Designs of graph echo state networks for node classification. - Alessio Micheli; Domenico Tortorella (Neurocomputing, 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)

Sensitivity Prediction on Protein Protein Interaction Networks. - Alessandro Dipalma; Michele Fontanesi; Alessio Micheli; Paolo Milazzo; Marco Podda (Zenodo, 2024)

Dynamical Properties of PPI Networks (DyPPIN). - Alessandro Dipalma; Paolo Milazzo; Alessio Micheli; Michele Fontanesi; Marco Podda (Zenodo, 2024)

Improving Antibody-Antigen Interaction Prediction Through Flexibility with ESMFold. - Sara Joubbi; Giuseppe Maccari; Giorgio Ciano; Alessio Micheli; Paolo Milazzo; Duccio Medini (BIOSTEC (1), 2025)

An Empirical Investigation of Shortcuts in Graph Learning. - Domenico Tortorella; Michele Fontanesi; Alessio Micheli; Marco Podda (GbRPR, 2025)

An empirical evaluation of rewiring approaches in graph neural networks. - Alessio Micheli; Domenico Tortorella (Pattern Recognit. Lett., 2025)

Learning to quantify graph nodes. - Alessio Micheli; Alejandro Moreo; Marco Podda; Fabrizio Sebastiani 001; William Simoni; Domenico Tortorella (CoRR, 2025)

Addressing the Scarcity of Benchmarks for Graph XAI. - Michele Fontanesi; Alessio Micheli; Marco Podda; Domenico Tortorella (CoRR, 2025)

Sensitivity analysis on protein-protein interaction networks through deep graph networks. - Alessandro Dipalma; Michele Fontanesi; Alessio Micheli; Paolo Milazzo; Marco Podda (BMC Bioinform., 2025)