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

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

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

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

Statistical Relational Learning for Proteomics: Function, Interactions and Evolution. - Stefano Teso (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)

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

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)

Elements of an Automatic Data Scientist. - Luc De Raedt; Hendrik Blockeel; Samuel Kolb; Stefano Teso; Gust Verbruggen (IDA, 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)

"Why Should I Trust Interactive Learners?" Explaining Interactive Queries of Classifiers to Users. - Stefano Teso; Kristian Kersting (CoRR, 2018)

Automating Personnel Rostering by Learning Constraints Using Tensors. - Mohit Kumar 003; Stefano Teso; Luc De Raedt (CoRR, 2018)

Explanatory Interactive Machine Learning. - Stefano Teso; Kristian Kersting (AIES, 2019)

Automating Personnel Rostering by Learning Constraints Using Tensors. - Mohit Kumar 003; Stefano Teso; Patrick De Causmaecker; Luc De Raedt (ICTAI, 2019)

Learning Linear Programs from Data. - Elias Arnold Schede; Samuel Kolb; Stefano Teso (ICTAI, 2019)

Acquiring Integer Programs from Data. - Mohit Kumar 003; Stefano Teso; Luc De Raedt (IJCAI, 2019)

SynthLog: A Language for Synthesising Inductive Data Models (Extended Abstract). - Yann Dauxais; Clément Gautrais; Anton Dries; Arcchit Jain; Samuel Kolb; Mohit Kumar 003; Stefano Teso; Elia Van Wolputte; Gust Verbruggen; Luc De Raedt (PKDD/ECML Workshops (1), 2019)

Constraint Learning: An Appetizer. - Stefano Teso (RW, 2019)

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

Does Symbolic Knowledge Prevent Adversarial Fooling? - Stefano Teso (CoRR, 2019)

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

Multi-Modal Subjective Context Modelling and Recognition. - Qiang Shen 005; Stefano Teso; Wanyi Zhang; Hao Xu 012; Fausto Giunchiglia (MRC@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)

VisualSynth: Democratizing Data Science in Spreadsheets. - Clément Gautrais; Yann Dauxais; Samuel Kolb; Arcchit Jain; Mohit Kumar 003; Stefano Teso; Elia Van Wolputte; Gust Verbruggen; Luc De Raedt (ECML/PKDD (5), 2020)

Right for the Wrong Scientific Reasons: Revising Deep Networks by Interacting with their Explanations. - Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting (CoRR, 2020)

Human-Machine Collaboration for Democratizing Data Science. - Clément Gautrais; Yann Dauxais; Stefano Teso; Samuel Kolb; Gust Verbruggen; Luc De Raedt (CoRR, 2020)

Toward Machine-Guided, Human-Initiated Explanatory Interactive Learning. - Teodora Popordanoska; Mohit Kumar 003; Stefano Teso (CoRR, 2020)

Machine Guides, Human Supervises: Interactive Learning with Global Explanations. - Teodora Popordanoska; Mohit Kumar 003; Stefano Teso (CoRR, 2020)

Challenges in Interactive Machine Learning. - Stefano Teso; Oliver Hinz (Künstliche Intell., 2020)

Predictive spreadsheet autocompletion with constraints. - Samuel Kolb; Stefano Teso; Anton Dries; Luc De Raedt (Mach. Learn., 2020)

Making deep neural networks right for the right scientific reasons by interacting with their explanations. - Patrick Schramowski; Wolfgang Stammer; Stefano Teso; Anna Brugger; Franziska Herbert; Xiaoting Shao; Hans-Georg Luigs; Anne-Katrin Mahlein; Kristian Kersting (Nat. Mach. Intell., 2020)

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 Compositional Atlas of Tractable Circuit Operations for Probabilistic Inference. - Antonio Vergari; YooJung Choi 001; Anji Liu; Stefano Teso; Guy Van den Broeck (NeurIPS, 2021)

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

Bandits for Learning to Explain from Explanations. - Freya Behrens; Stefano Teso; Davide Mottin (CoRR, 2021)

A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries. - Antonio Vergari; YooJung Choi 001; Anji Liu; Stefano Teso; Guy Van den Broeck (CoRR, 2021)

Learning Mixed-Integer Linear Programs from Contextual Examples. - Mohit Kumar 003; Samuel Kolb; Luc De Raedt; Stefano Teso (CoRR, 2021)

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

Human-Machine Collaboration for Democratizing Data Science. - Clément Gautrais; Yann Dauxais; Stefano Teso; Samuel Kolb; Gust Verbruggen; Luc De Raedt (Human-Like Machine Intelligence, 2022)

Machine Learning for Utility Prediction in Argument-Based Computational Persuasion. - Ivan Donadello; Anthony Hunter; Stefano Teso; Mauro Dragoni (AAAI, 2022)

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

Federated Multi-Task Attention for Cross-Individual Human Activity Recognition. - Qiang Shen 005; Haotian Feng; Rui Song 008; Stefano Teso; Fausto Giunchiglia; Hao Xu 012 (IJCAI, 2022)

Semantic Probabilistic Layers for Neuro-Symbolic Learning. - Kareem Ahmed; Stefano Teso; Kai-Wei Chang; Guy Van den Broeck; Antonio Vergari (NeurIPS, 2022)

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

Efficient and Reliable Probabilistic Interactive Learning with Structured Outputs. - Stefano Teso; Antonio Vergari (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)

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)

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

A Dataset for Utility Prediction in Computational Persuasion with Machine Learning Techniques. - Ivan Donadello; Anthony Hunter; Stefano Teso; Mauro Dragoni (Zenodo, 2022)

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)

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)

Learning MAX-SAT from contextual examples for combinatorial optimisation. - Mohit Kumar 003; Samuel Kolb; Stefano Teso; Luc De Raedt (Artif. Intell., 2023)

Learning to Guide Human Experts via Personalized Large Language Models. - Debodeep Banerjee; Stefano Teso; Andrea Passerini (CoRR, 2023)

How Faithful are Self-Explainable GNNs? - Marc Christiansen; Lea Villadsen; Zhiqiang Zhong; Stefano Teso; Davide Mottin (CoRR, 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)

Leveraging explanations in interactive machine learning: An overview. - Stefano Teso; Öznur Alkan; Wolfgang Stammer; Elizabeth Daly (Frontiers Artif. Intell., 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)

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)

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

Towards Logically Consistent Language Models via Probabilistic Reasoning. - Diego Calanzone; Stefano Teso; Antonio Vergari (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)

Spurious Correlations in Concept Drift: Can Explanatory Interaction Help? - Cristiana Lalletti; Stefano Teso (CoRR, 2024)

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

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)

Logically Consistent Language Models via Neuro-Symbolic Integration. - Diego Calanzone; Stefano Teso; Antonio Vergari (ICLR, 2025)

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

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)

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)

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

Learning to Reject Low-Quality Explanations via User Feedback. - Luca Stradiotti; Dario Pesenti; Stefano Teso; Jesse Davis (CoRR, 2025)