Evaluation Methods for Focused Crawling. - Andrea Passerini; Paolo Frasconi; Giovanni Soda (AI*IA, 2001)

From Margins to Probabilities in Multiclass Learning Problems. - Andrea Passerini; Massimiliano Pontil; Paolo Frasconi (ECAI, 2002)

A two-stage SVM architecture for predicting the disulfide bonding state of cysteines. - Paolo Frasconi; Andrea Passerini; Alessandro Vullo (NNSP, 2002)

A Combination of Support Vector Machines and Bidirectional Recurrent Neural Networks for Protein Secondary Structure Prediction. - Alessio Ceroni; Paolo Frasconi; Andrea Passerini; Alessandro Vullo (AI*IA, 2003)

Predicting the Disulfide Bonding State of Cysteines with Combinations of Kernel Machines. - Alessio Ceroni; Paolo Frasconi; Andrea Passerini; Alessandro Vullo (J. VLSI Signal Process., 2003)

New results on error correcting output codes of kernel machines. - Andrea Passerini; Massimiliano Pontil; Paolo Frasconi (IEEE Trans. Neural Networks, 2004)

Kernel methods, multiclass classification and applications to computational molecular biology. - Andrea Passerini (2004)

Automatic semantics extraction in law documents. - Carlo Biagioli; Enrico Francesconi; Andrea Passerini; Simonetta Montemagni; Claudia Soria (ICAIL, 2005)

Kernels on Prolog Ground Terms. - Andrea Passerini; Paolo Frasconi (IJCAI, 2005)

kFOIL: Learning Simple Relational Kernels. - Niels Landwehr; Andrea Passerini; Luc De Raedt; Paolo Frasconi (AAAI, 2006)

Decomposition Kernels for Natural Language Processing. - Fabrizio Costa; Sauro Menchetti; Alessio Ceroni; Andrea Passerini; Paolo Frasconi (Learning Structured Information@EACL, 2006)

Improving Prediction of Zinc Binding Sites by Modeling the Linkage Between Residues Close in Sequence. - Sauro Menchetti; Andrea Passerini; Paolo Frasconi; Claudia Andreini; Antonio Rosato (RECOMB, 2006)

Kernels on Prolog Proof Trees: Statistical Learning in the ILP Setting. - Andrea Passerini; Paolo Frasconi; Luc De Raedt (J. Mach. Learn. Res., 2006)

DISULFIND: a disulfide bonding state and cysteine connectivity prediction server. - Alessio Ceroni; Andrea Passerini; Alessandro Vullo; Paolo Frasconi (Nucleic Acids Res., 2006)

Automatic Classification of Provisions in Legislative Texts. - Enrico Francesconi; Andrea Passerini (Artif. Intell. Law, 2007)

Predicting zinc binding at the proteome level. - Andrea Passerini; Claudia Andreini; Sauro Menchetti; Antonio Rosato; Paolo Frasconi (BMC Bioinform., 2007)

On the Convergence of Protein Structure and Dynamics. Statistical Learning Studies of Pseudo Folding Pathways. - Alessandro Vullo; Andrea Passerini; Paolo Frasconi; Fabrizio Costa; Gianluca Pollastri (EvoBIO, 2008)

Feature Discovery with Type Extension Trees. - Paolo Frasconi; Manfred Jaeger; Andrea Passerini (ILP, 2008)

Learning with Kernels and Logical Representations. - Paolo Frasconi; Andrea Passerini (Probabilistic Inductive Logic Programming, 2008)

Predicting the Geometry of Metal Binding Sites from Protein Sequence. - Paolo Frasconi; Andrea Passerini (NIPS, 2008)

A semiparametric generative model for efficient structured-output supervised learning. - Fabrizio Costa; Andrea Passerini; Marco Lippi 001; Paolo Frasconi (Ann. Math. Artif. Intell., 2008)

MetalDetector: a web server for predicting metal-binding sites and disulfide bridges in proteins from sequence. - Marco Lippi 001; Andrea Passerini; Marco Punta; Burkhard Rost; Paolo Frasconi (Bioinform., 2008)

A simplified approach to disulfide connectivity prediction from protein sequences. - Marc Vincent; Andrea Passerini; Matthieu Labbé; Paolo Frasconi (BMC Bioinform., 2008)

Predicting Structural and Functional Sites in Proteins by Searching for Maximum-weight Cliques. - Franco Mascia; Elisa Cilia; Mauro Brunato; Andrea Passerini (AAAI, 2010)

From On-Going to Complete Activity Recognition Exploiting Related Activities. - Carlo Nicolini; Bruno Lepri; Stefano Teso; Andrea Passerini (HBU, 2010)

Adapting to a Realistic Decision Maker: Experiments towards a Reactive Multi-objective Optimizer. - Paolo Campigotto; Andrea Passerini (LION, 2010)

An On/Off Lattice Approach to Protein Structure Prediction from Contact Maps. - Stefano Teso; Cristina Di Risio; Andrea Passerini; Roberto Battiti (PRIB, 2010)

Automatic prediction of catalytic residues by modeling residue structural neighborhood. - Elisa Cilia; Andrea Passerini (BMC Bioinform., 2010)

Fast learning of relational kernels. - Niels Landwehr; Andrea Passerini; Luc De Raedt; Paolo Frasconi (Mach. Learn., 2010)

Brain-Computer Evolutionary Multiobjective Optimization: A Genetic Algorithm Adapting to the Decision Maker. - Roberto Battiti; Andrea Passerini (IEEE Trans. Evol. Comput., 2010)

Active Learning of Combinatorial Features for Interactive Optimization. - Paolo Campigotto; Andrea Passerini; Roberto Battiti (LION, 2011)

Relational Feature Mining with Hierarchical Multitask kFOIL. - Elisa Cilia; Niels Landwehr; Andrea Passerini (Fundam. Informaticae, 2011)

Relational information gain. - Marco Lippi 001; Manfred Jaeger; Paolo Frasconi; Andrea Passerini (Mach. Learn., 2011)

MetalDetector v2.0: predicting the geometry of metal binding sites from protein sequence. - Andrea Passerini; Marco Lippi 001; Paolo Frasconi (Nucleic Acids Res., 2011)

Using Machine Learning and Information Retrieval Techniques to Improve Software Maintainability. - Anna Corazza; Sergio Di Martino; Valerio Maggio; Alessandro Moschitti; Andrea Passerini; Giuseppe Scanniello; Fabrizio Silvestri (EternalS@ECAI, 2012)

Predicting virus mutations through relational learning. - Elisa Cilia; Stefano Teso; Sergio Ammendola; Tom Lenaerts; Andrea Passerini (AIMM, 2012)

Improving activity recognition by segmental pattern mining. - Umut Avci; Andrea Passerini (PerCom Workshops, 2012)

Metal Binding in Proteins: Machine Learning Complements X-Ray Absorption Spectroscopy. - Marco Lippi 001; Andrea Passerini; Marco Punta; Paolo Frasconi (ECML/PKDD (2), 2012)

Predicting Metal-Binding Sites from Protein Sequence. - Andrea Passerini; Marco Lippi 001; Paolo Frasconi (IEEE ACM Trans. Comput. Biol. Bioinform., 2012)

Navigating the topical structure of academic search results via the Wikipedia category network. - Daniil Mirylenka; Andrea Passerini (CIKM, 2013)

A Fully Unsupervised Approach to Activity Discovery. - Umut Avci; Andrea Passerini (HBU, 2013)

ScienScan - An Efficient Visualization and Browsing Tool for Academic Search. - Daniil Mirylenka; Andrea Passerini (ECML/PKDD (3), 2013)

Ego-centric Graphlets for Personality and Affective States Recognition. - Stefano Teso; Jacopo Staiano; Bruno Lepri; Andrea Passerini; Fabio Pianesi (SocialCom, 2013)

Type Extension Trees for feature construction and learning in relational domains. - Manfred Jaeger; Marco Lippi 001; Andrea Passerini; Paolo Frasconi (Artif. Intell., 2013)

Kernel Methods for Structured Data. - Andrea Passerini (Handbook on Neural Information Processing, 2013)

Predicting virus mutations through statistical relational learning. - Elisa Cilia; Stefano Teso; Sergio Ammendola; Tom Lenaerts; Andrea Passerini (BMC Bioinform., 2014)

Improved multi-level protein¿protein interaction prediction with semantic-based regularization. - Claudio Saccà; Stefano Teso; Michelangelo Diligenti; Andrea Passerini (BMC Bioinform., 2014)

Joint probabilistic-logical refinement of multiple protein feature predictors. - Stefano Teso; Andrea Passerini (BMC Bioinform., 2014)

Hybrid SRL with Optimization Modulo Theories. - Stefano Teso; Roberto Sebastiani; Andrea Passerini (CoRR, 2014)

Improving Activity Recognitionby Segmental Pattern Mining. - Umut Avci; Andrea Passerini (IEEE Trans. Knowl. Data Eng., 2014)

Active Learning of Pareto Fronts. - Paolo Campigotto; Andrea Passerini; Roberto Battiti (IEEE Trans. Neural Networks Learn. Syst., 2014)

Probabilistic Inference in Hybrid Domains by Weighted Model Integration. - Vaishak Belle; Andrea Passerini; Guy Van den Broeck (IJCAI, 2015)

Bootstrapping Domain Ontologies from Wikipedia: A Uniform Approach. - Daniil Mirylenka; Andrea Passerini; Luciano Serafini (IJCAI, 2015)

Hashing-Based Approximate Probabilistic Inference in Hybrid Domains. - Vaishak Belle; Guy Van den Broeck; Andrea Passerini (UAI, 2015)

Learning Modulo Theories for preference elicitation in hybrid domains. - Paolo Campigotto; Roberto Battiti; Andrea Passerini (CoRR, 2015)

Component Caching in Hybrid Domains with Piecewise Polynomial Densities. - Vaishak Belle; Guy Van den Broeck; Andrea Passerini (AAAI, 2016)

Classtering: Joint Classification and Clustering with Mixture of Factor Analysers. - Emanuele Sansone; Andrea Passerini; Francesco G. B. De Natale (ECAI, 2016)

Hashing-Based Approximate Probabilistic Inference in Hybrid Domains: An Abridged Report. - Vaishak Belle; Guy Van den Broeck; Andrea Passerini (IJCAI, 2016)

Constructive Preference Elicitation by Setwise Max-Margin Learning. - Stefano Teso; Andrea Passerini; Paolo Viappiani (IJCAI, 2016)

RNAcommender: genome-wide recommendation of RNA-protein interactions. - Gianluca Corrado; Toma Tebaldi; Fabrizio Costa; Paolo Frasconi; Andrea Passerini (Bioinform., 2016)

Guest editors' introduction to the EcmlPkdd 2016 journal track special issue of Machine Learning. - Thomas Gärtner 001; Mirco Nanni; Andrea Passerini; Céline Robardet (Mach. Learn., 2016)

Learning Modulo Theories. - Andrea Passerini (Data Mining and Constraint Programming, 2016)

Coactive Critiquing: Elicitation of Preferences and Features. - Stefano Teso; Paolo Dragone; Andrea Passerini (AAAI, 2017)

Constructive Preference Elicitation for Multiple Users with Setwise Max-margin. - Stefano Teso; Andrea Passerini; Paolo Viappiani (ADT, 2017)

Efficient Weighted Model Integration via SMT-Based Predicate Abstraction. - Paolo Morettin; Andrea Passerini; Roberto Sebastiani (IJCAI, 2017)

Introduction to the special issue on Combining Constraint Solving with Mining and Learning. - Andrea Passerini; Guido Tack; Tias Guns (Artif. Intell., 2017)

Structured learning modulo theories. - Stefano Teso; Roberto Sebastiani; Andrea Passerini (Artif. Intell., 2017)

Constructive Preference Elicitation. - Paolo Dragone; Stefano Teso; Andrea Passerini (Frontiers Robotics AI, 2017)

Decomposition Strategies for Constructive Preference Elicitation. - Paolo Dragone; Stefano Teso; Mohit Kumar 003; Andrea Passerini (AAAI, 2018)

Constructive Preference Elicitation Over Hybrid Combinatorial Spaces. - Paolo Dragone; Stefano Teso; Andrea Passerini (AAAI, 2018)

Learning Constraints From Examples. - Luc De Raedt; Andrea Passerini; Stefano Teso (AAAI, 2018)

Pyconstruct: Constraint Programming Meets Structured Prediction. - Paolo Dragone; Stefano Teso; Andrea Passerini (IJCAI, 2018)

Learning SMT(LRA) Constraints using SMT Solvers. - Samuel Kolb; Stefano Teso; Andrea Passerini; Luc De Raedt (IJCAI, 2018)

Automating Layout Synthesis with Constructive Preference Elicitation. - Luca Erculiani; Paolo Dragone; Stefano Teso; Andrea Passerini (ECML/PKDD (3), 2018)

No more ready-made deals: constructive recommendation for telco service bundling. - Paolo Dragone; Giovanni Pellegrini; Michele Vescovi; Katya Tentori; Andrea Passerini (RecSys, 2018)

The pywmi Framework and Toolbox for Probabilistic Inference using Weighted Model Integration. - Samuel Kolb; Paolo Morettin; Pedro Zuidberg Dos Martires; Francesco Sommavilla; Andrea Passerini; Roberto Sebastiani; Luc De Raedt (IJCAI, 2019)

Advanced SMT techniques for weighted model integration. - Paolo Morettin; Andrea Passerini; Roberto Sebastiani (Artif. Intell., 2019)

Combining learning and constraints for genome-wide protein annotation. - Stefano Teso; Luca Masera; Michelangelo Diligenti; Andrea Passerini (BMC Bioinform., 2019)

Counts-of-counts similarity for prediction and search in relational data. - Manfred Jaeger; Marco Lippi 001; Giovanni Pellegrini; Andrea Passerini (Data Min. Knowl. Discov., 2019)

Special issue: Selected and revised papers from the 17th International Conference of the Italian Association for Artificial Intelligence. - Chiara Ghidini; Bernardo Magnini; Andrea Passerini (Intelligenza Artificiale, 2019)

Fixing Mislabeling by Human Annotators Leveraging Conflict Resolution and Prior Knowledge. - Mattia Zeni; Wanyi Zhang; Enrico Bignotti; Andrea Passerini; Fausto Giunchiglia (Proc. ACM Interact. Mob. Wearable Ubiquitous Technol., 2019)

A Big Data and machine learning approach for network monitoring and security. - Leonardo Maccari; Andrea Passerini (Secur. Priv., 2019)

Learning Weighted Model Integration Distributions. - Paolo Morettin; Samuel Kolb; Stefano Teso; Andrea Passerini (AAAI, 2020)

Continual Egocentric Object Recognition. - Luca Erculiani; Fausto Giunchiglia; Andrea Passerini (ECAI, 2020)

Learning in the Wild with Incremental Skeptical Gaussian Processes. - Andrea Bontempelli; Stefano Teso; Fausto Giunchiglia; Andrea Passerini (IJCAI, 2020)

Efficient Generation of Structured Objects with Constrained Adversarial Networks. - Luca Di Liello; Pierfrancesco Ardino; Jacopo Gobbi; Paolo Morettin; Stefano Teso; Andrea Passerini (NeurIPS, 2020)

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. - Mirco Nanni; Gennady L. Andrienko; Albert-László Barabási; Chiara Boldrini; Francesco Bonchi; Ciro Cattuto; Francesca Chiaromonte; Giovanni Comandè; Marco Conti; Mark Coté; Frank Dignum; Virginia Dignum; et al. (CoRR, 2020)

Few-Shot Unsupervised Continual Learning through Meta-Examples. - Alessia Bertugli; Stefano Vincenzi; Simone Calderara; Andrea Passerini (CoRR, 2020)

Dealing with Mislabeling via Interactive Machine Learning. - Wanyi Zhang; Andrea Passerini; Fausto Giunchiglia (Künstliche Intell., 2020)

Deep Learning for Classification and Localization of COVID-19 Markers in Point-of-Care Lung Ultrasound. - Subhankar Roy; Willi Menapace; Sebastiaan Oei; Ben Luijten; Enrico Fini; Cristiano Saltori; Iris A. M. Huijben; Nishith Chennakeshava; Federico Mento; Alessandro Sentelli; Emanuele Peschiera; Riccardo Trevisan; et al. (IEEE Trans. Medical Imaging, 2020)

Hybrid Probabilistic Inference with Logical and Algebraic Constraints: a Survey. - Paolo Morettin; Pedro Zuidberg Dos Martires; Samuel Kolb; Andrea Passerini (IJCAI, 2021)

Learning Aggregation Functions. - Giovanni Pellegrini; Alessandro Tibo; Paolo Frasconi; Andrea Passerini; Manfred Jaeger (IJCAI, 2021)

Co-creating Platformer Levels with Constrained Adversarial Networks. - Paolo Morettin; Andrea Passerini; Stefano Teso (IUI Workshops, 2021)

Neuro-Symbolic Constraint Programming for Structured Prediction. - Paolo Dragone; Stefano Teso; Andrea Passerini (NeSy, 2021)

Interactive Label Cleaning with Example-based Explanations. - Stefano Teso; Andrea Bontempelli; Fausto Giunchiglia; Andrea Passerini (NeurIPS, 2021)

A Neuro-Symbolic Approach to Structured Event Recognition. - Gianluca Apriceno; Andrea Passerini; Luciano Serafini (TIME, 2021)

Learning Modulo Theories for constructive preference elicitation. - Paolo Campigotto; Stefano Teso; Roberto Battiti; Andrea Passerini (Artif. Intell., 2021)

A review and experimental analysis of active learning over crowdsourced data. - Burcu Sayin; Evgeny Krivosheev; Jie Yang 028; Andrea Passerini; Fabio Casati (Artif. Intell. Rev., 2021)

Learning compositional programs with arguments and sampling. - Giovanni De Toni; Luca Erculiani; Andrea Passerini (CoRR, 2021)

Toward a Unified Framework for Debugging Gray-box Models. - Andrea Bontempelli; Fausto Giunchiglia; Andrea Passerini; Stefano Teso (CoRR, 2021)

The Science of Rejection: A Research Area for Human Computation. - Burcu Sayin; Jie Yang 028; Andrea Passerini; Fabio Casati (CoRR, 2021)

Putting human behavior predictability in context. - Wanyi Zhang; Qiang Shen 005; Stefano Teso; Bruno Lepri; Andrea Passerini; Ivano Bison; Fausto Giunchiglia (EPJ Data Sci., 2021)

Give more data, awareness and control to individual citizens, and they will help COVID-19 containment. - Mirco Nanni; Gennady L. Andrienko; Albert-László Barabási; Chiara Boldrini; Francesco Bonchi; Ciro Cattuto; Francesca Chiaromonte; Giovanni Comandè; Marco Conti; Mark Coté; Frank Dignum; Virginia Dignum; et al. (Ethics Inf. Technol., 2021)

Towards Visual Semantics. - Fausto Giunchiglia; Luca Erculiani; Andrea Passerini (SN Comput. Sci., 2021)

Catastrophic Forgetting in Continual Concept Bottleneck Models. - Emanuele Marconato; Gianpaolo Bontempo; Stefano Teso; Elisa Ficarra; Simone Calderara; Andrea Passerini (ICIAP Workshops, 2022)

Generalising via Meta-examples for Continual Learning in the Wild. - Alessia Bertugli; Stefano Vincenzi; Simone Calderara; Andrea Passerini (LOD (1), 2022)

GlanceNets: Interpretable, Leak-proof Concept-based Models. - Emanuele Marconato; Andrea Passerini; Stefano Teso (NeurIPS, 2022)

A Neuro-Symbolic Approach for Real-World Event Recognition from Weak Supervision. - Gianluca Apriceno; Andrea Passerini; Luciano Serafini (TIME, 2022)

SMT-based weighted model integration with structure awareness. - Giuseppe Spallitta; Gabriele Masina; Paolo Morettin; Andrea Passerini; Roberto Sebastiani (UAI, 2022)

Skeptical Learning - An Algorithm and a Platform for Dealing with Mislabeling in Personal Context Recognition. - Wanyi Zhang; Mattia Zeni; Andrea Passerini; Fausto Giunchiglia (Algorithms, 2022)

Neighbourhood matching creates realistic surrogate temporal networks. - Antonio Longa; Giulia Cencetti; Sune Lehmann; Andrea Passerini; Bruno Lepri (CoRR, 2022)

Lifelong Personal Context Recognition. - Andrea Bontempelli; Marcelo Dario Rodas Britez; Xiaoyue Li; Haonan Zhao; Luca Erculiani; Stefano Teso; Andrea Passerini; Fausto Giunchiglia (CoRR, 2022)

Machine Learning for Combinatorial Optimisation of Partially-Specified Problems: Regret Minimisation as a Unifying Lens. - Stefano Teso; Laurens Bliek; Andrea Borghesi; Michele Lombardi 001; Neil Yorke-Smith; Tias Guns; Andrea Passerini (CoRR, 2022)

Generating personalized counterfactual interventions for algorithmic recourse by eliciting user preferences. - Giovanni De Toni; Paolo Viappiani; Bruno Lepri; Andrea Passerini (CoRR, 2022)

GlanceNets: Interpretabile, Leak-proof Concept-based Models. - Emanuele Marconato; Andrea Passerini; Stefano Teso (CoRR, 2022)

Concept-level Debugging of Part-Prototype Networks. - Andrea Bontempelli; Stefano Teso; Fausto Giunchiglia; Andrea Passerini (CoRR, 2022)

Rethinking and Recomputing the Value of ML Models. - Burcu Sayin; Fabio Casati; Andrea Passerini; Jie Yang 028; Xinyue Chen (CoRR, 2022)

Human-in-the-loop handling of knowledge drift. - Andrea Bontempelli; Fausto Giunchiglia; Andrea Passerini; Stefano Teso (Data Min. Knowl. Discov., 2022)

An efficient procedure for mining egocentric temporal motifs. - Antonio Longa; Giulia Cencetti; Bruno Lepri; Andrea Passerini (Data Min. Knowl. Discov., 2022)

A Neuro-Symbolic Approach for Non-Intrusive Load Monitoring. - Gianluca Apriceno; Luca Erculiani; Andrea Passerini (ECAI, 2023)

Environmentally-Aware Bundle Recommendation Using the Choquet Integral. - Marco Bronzini; Erich Robbi; Paolo Viappiani; Andrea Passerini (ECAI, 2023)

Egocentric Hierarchical Visual Semantics. - Luca Erculiani; Andrea Bontempelli; Andrea Passerini; Fausto Giunchiglia (HHAI, 2023)

Value-Aware Active Learning. - Burcu Sayin; Jie Yang 028; Andrea Passerini; Fabio Casati (HHAI, 2023)

Value-Based Hybrid Intelligence. - Burcu Sayin; Jie Yang 028; Andrea Passerini; Fabio Casati (HHAI, 2023)

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

Concept-level Debugging of Part-Prototype Networks. - Andrea Bontempelli; Stefano Teso; Katya Tentori; Fausto Giunchiglia; Andrea Passerini (ICLR, 2023)

Neuro-Symbolic Continual Learning: Knowledge, Reasoning Shortcuts and Concept Rehearsal. - Emanuele Marconato; Gianpaolo Bontempo; Elisa Ficarra; Simone Calderara; Andrea Passerini; Stefano Teso (ICML, 2023)

Meta-Path Learning for Multi-Relational Graph Neural Networks. - Francesco Ferrini; Antonio Longa; Andrea Passerini; Manfred Jaeger (LoG, 2023)

A Simple Latent Variable Model for Graph Learning and Inference. - Manfred Jaeger; Antonio Longa; Steve Azzolin; Oliver Schulte; Andrea Passerini (LoG, 2023)

Generalized Reasoning With Graph Neural Networks by Relational Bayesian Network Encodings. - Raffaele Pojer; Andrea Passerini; Manfred Jaeger (LoG, 2023)

Neuro-Symbolic Reasoning Shortcuts: Mitigation Strategies and their Limitations. - Emanuele Marconato; Stefano Teso; Andrea Passerini (NeSy, 2023)

Not All Neuro-Symbolic Concepts Are Created Equal: Analysis and Mitigation of Reasoning Shortcuts. - Emanuele Marconato; Stefano Teso; Antonio Vergari; Andrea Passerini (NeurIPS, 2023)

Interval Logic Tensor Networks. - Samy Badreddine; Gianluca Apriceno; Andrea Passerini; Luciano Serafini (CoRR, 2023)

Learning to Guide Human Experts via Personalized Large Language Models. - Debodeep Banerjee; Stefano Teso; Andrea Passerini (CoRR, 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)

Semantic Loss Functions for Neuro-Symbolic Structured Prediction. - Kareem Ahmed; Stefano Teso; Paolo Morettin; Luca Di Liello; Pierfrancesco Ardino; Jacopo Gobbi; Yitao Liang; Eric Wang; Kai-Wei Chang; Andrea Passerini; Guy Van den Broeck (Compendium of Neurosymbolic Artificial Intelligence, 2023)

Synthesizing explainable counterfactual policies for algorithmic recourse with program synthesis. - Giovanni De Toni; Bruno Lepri; Andrea Passerini (Mach. Learn., 2023)

Interpretability Is in the Mind of the Beholder: A Causal Framework for Human-Interpretable Representation Learning. - Emanuele Marconato; Andrea Passerini; Stefano Teso (Entropy, 2023)

Adaptation of student behavioural routines during Covid-19: a multimodal approach. - Nicolò Alessandro Girardini; Simone Centellegher; Andrea Passerini; Ivano Bison; Fausto Giunchiglia; Bruno Lepri (EPJ Data Sci., 2023)

Can LLMs Correct Physicians, Yet? Investigating Effective Interaction Methods in the Medical Domain. - Burcu Sayin; Pasquale Minervini; Jacopo Staiano; Andrea Passerini (ClinicalNLP@NAACL, 2024)

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

A Neuro-Symbolic Benchmark Suite for Concept Quality and Reasoning Shortcuts. - Samuele Bortolotti; Emanuele Marconato; Tommaso Carraro; Paolo Morettin; Emile van Krieken; Antonio Vergari; Stefano Teso; Andrea Passerini (NeurIPS, 2024)

BEARS Make Neuro-Symbolic Models Aware of their Reasoning Shortcuts. - Emanuele Marconato; Samuele Bortolotti; Emile van Krieken; Antonio Vergari; Andrea Passerini; Stefano Teso (UAI, 2024)

Preference Elicitation in Interactive and User-centered Algorithmic Recourse: an Initial Exploration. - Seyedehdelaram Esfahani; Giovanni De Toni; Bruno Lepri; Andrea Passerini; Katya Tentori; Massimo Zancanaro (UMAP, 2024)

A Unified Framework for Probabilistic Verification of AI Systems via Weighted Model Integration. - Paolo Morettin; Andrea Passerini; Roberto Sebastiani (CoRR, 2024)

Learning To Guide Human Decision Makers With Vision-Language Models. - Debodeep Banerjee; Stefano Teso; Burcu Sayin; Andrea Passerini (CoRR, 2024)

Unveiling LLMs: The Evolution of Latent Representations in a Temporal Knowledge Graph. - Marco Bronzini; Carlo Nicolini; Bruno Lepri; Jacopo Staiano; Andrea Passerini (CoRR, 2024)

Exploiting Preference Elicitation in Interactive and User-centered Algorithmic Recourse: An Initial Exploration. - Seyedehdelaram Esfahani; Giovanni De Toni; Bruno Lepri; Andrea Passerini; Katya Tentori; Massimo Zancanaro (CoRR, 2024)

Semantic Loss Functions for Neuro-Symbolic Structured Prediction. - Kareem Ahmed; Stefano Teso; Paolo Morettin; Luca Di Liello; Pierfrancesco Ardino; Jacopo Gobbi; Yitao Liang; Eric Wang; Kai-Wei Chang; Andrea Passerini; Guy Van den Broeck (CoRR, 2024)

A Benchmark Suite for Systematically Evaluating Reasoning Shortcuts. - Samuele Bortolotti; Emanuele Marconato; Tommaso Carraro; Paolo Morettin; Emile van Krieken; Antonio Vergari; Stefano Teso; Andrea Passerini (CoRR, 2024)

Perks and Pitfalls of Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs. - Steve Azzolin; Antonio Longa; Stefano Teso; Andrea Passerini (CoRR, 2024)

Benchmarking XAI Explanations with Human-Aligned Evaluations. - Rémi Kazmierczak; Steve Azzolin; Eloïse Berthier; Anna Hedström; Patricia Delhomme; Nicolas Bousquet 001; Goran Frehse; Massimiliano Mancini; Baptiste Caramiaux; Andrea Passerini; Gianni Franchi (CoRR, 2024)

Fostering effective hybrid human-LLM reasoning and decision making. - Andrea Passerini; Aryo Gema; Pasquale Minervini; Burcu Sayin; Katya Tentori (Frontiers Artif. Intell., 2024)

Personalized bundle recommendation using preference elicitation and the Choquet integral. - Erich Robbi; Marco Bronzini; Paolo Viappiani; Andrea Passerini (Frontiers Artif. Intell., 2024)

Personalized Algorithmic Recourse with Preference Elicitation. - Giovanni De Toni; Paolo Viappiani; Stefano Teso; Bruno Lepri; Andrea Passerini (Trans. Mach. Learn. Res., 2024)

Enhancing SMT-based Weighted Model Integration by structure awareness. - Giuseppe Spallitta; Gabriele Masina; Paolo Morettin; Andrea Passerini; Roberto Sebastiani (Artif. Intell., 2024)

A Benchmark Suite for Systematically Evaluating Reasoning Shortcuts. - Samuele Bortolotti; Emanuele Marconato; Tommaso Carraro; Paolo Morettin; Emile van Krieken; Antonio Vergari; Stefano Teso; Andrea Passerini (Zenodo, 2024)

Glitter or gold? Deriving structured insights from sustainability reports via large language models. - Marco Bronzini; Carlo Nicolini; Bruno Lepri; Andrea Passerini; Jacopo Staiano (EPJ Data Sci., 2024)

Time Can Invalidate Algorithmic Recourse. - Giovanni De Toni; Stefano Teso; Bruno Lepri; Andrea Passerini (FAccT, 2025)

Reconsidering Faithfulness in Regular, Self-Explainable and Domain Invariant GNNs. - Steve Azzolin; Antonio Longa; Stefano Teso; Andrea Passerini (ICLR, 2025)

A Probabilistic Neuro-symbolic Layer for Algebraic Constraint Satisfaction. - Leander Kurscheidt; Paolo Morettin; Roberto Sebastiani; Andrea Passerini; Antonio Vergari (UAI, 2025)

Bringing Machine Learning Classifiers Into Critical Cyber-Physical Systems: A Matter of Design. - Burcu Sayin; Tommaso Zoppi; Nicolò Marchini; Fahad Ahmed KhoKhar; Andrea Passerini (IEEE Access, 2025)

A Self-Explainable Heterogeneous GNN for Relational Deep Learning. - Francesco Ferrini; Antonio Longa; Andrea Passerini; Manfred Jaeger (Trans. Mach. Learn. Res., 2025)

Community Aware Temporal Network Generation. - Nicolò Alessandro Girardini; Antonio Longa; Gaia Trebucchi; Giulia Cencetti; Andrea Passerini; Bruno Lepri (CoRR, 2025)

Beyond Topological Self-Explainable GNNs: A Formal Explainability Perspective. - Steve Azzolin; Sagar Malhotra; Andrea Passerini; Stefano Teso (CoRR, 2025)

Simple Path Structural Encoding for Graph Transformers. - Louis Airale; Antonio Longa; Mattia Rigon; Andrea Passerini; Roberto Passerone (CoRR, 2025)

Shortcuts and Identifiability in Concept-based Models from a Neuro-Symbolic Lens. - Samuele Bortolotti; Emanuele Marconato; Paolo Morettin; Andrea Passerini; Stefano Teso (CoRR, 2025)

Noiser: Bounded Input Perturbations for Attributing Large Language Models. - Mohammad Reza Ghasemi Madani; Aryo Pradipta Gema; Gabriele Sarti; Yu Zhao 043; Pasquale Minervini; Andrea Passerini (CoRR, 2025)

Boosting Relational Deep Learning with Pretrained Tabular Models. - Veronica Lachi; Antonio Longa; Beatrice Bevilacqua; Bruno Lepri; Andrea Passerini; Bruno Ribeiro 001 (CoRR, 2025)

If Concept Bottlenecks are the Question, are Foundation Models the Answer? - Nicola Debole; Pietro Barbiero; Francesco Giannini; Andrea Passerini; Stefano Teso; Emanuele Marconato (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)

Personalized Interpretability - Interactive Alignment of Prototypical Parts Networks. - Tomasz Michalski 002; Adam Wróbel; Andrea Bontempelli; Jakub Lustyk; Mikolaj Kniejski; Stefano Teso; Andrea Passerini; Bartosz Zielinski 001; Dawid Rymarczyk (CoRR, 2025)

MedSyn: Enhancing Diagnostics with Human-AI Collaboration. - Burcu Sayin; Ipek Baris Schlicht; Ngoc Vo Hong; Sara Allievi; Jacopo Staiano; Pasquale Minervini; Andrea Passerini (CoRR, 2025)

Bridging Theory and Practice in Link Representation with Graph Neural Networks. - Veronica Lachi; Francesco Ferrini; Antonio Longa; Bruno Lepri; Andrea Passerini; Manfred Jaeger (CoRR, 2025)

MedGellan: LLM-Generated Medical Guidance to Support Physicians. - Debodeep Banerjee; Burcu Sayin; Stefano Teso; Andrea Passerini (CoRR, 2025)

GNNs Meet Sequence Models Along the Shortest-Path: an Expressive Method for Link Prediction. - Francesco Ferrini; Veronica Lachi; Antonio Longa; Bruno Lepri; Andrea Passerini (CoRR, 2025)

Boosting Team Modeling through Tempo-Relational Representation Learning. - Vincenzo Marco De Luca; Giovanna Varni; Andrea Passerini (CoRR, 2025)

You Don't Bring Me Flowers: Mitigating Unwanted Recommendations Through Conformal Risk Control. - Giovanni De Toni; Erasmo Purificato; Emilia Gómez; Bruno Lepri; Andrea Passerini; Cristian Consonni (CoRR, 2025)

A Neuro-Symbolic Approach for Probabilistic Reasoning on Graph Data. - Raffaele Pojer; Andrea Passerini; Kim G. Larsen; Manfred Jaeger (CoRR, 2025)

Rethinking and recomputing the value of machine learning models. - Burcu Sayin; Jie Yang 028; Xinyue Chen; Andrea Passerini; Fabio Casati (Artif. Intell. Rev., 2025)