Stefano Teso

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Andrea PasseriniAssociate Professor, University of TrentoVerified email at disi.unitn.it
Luc De Raedtprofessor, KU Leuven & guestprofessor, Örebro UniversityVerified email at cs.kuleuven.be
Fausto GiunchigliaProfessor of Computer Science, Università di TrentoVerified email at unitn.it
Samuel KolbKU LeuvenVerified email at kuleuven.be
Antonio VergariReader (Associate Professor), University of Edinburgh, UKVerified email at ed.ac.uk
Paolo DragoneTwitterVerified email at twitter.com
Kristian KerstingProfessor of AI & ML, TU Darmstadt, Co-Director hessian.ai, DFKI, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
Mohit KumarPhD Student, KU LeuvenVerified email at cs.kuleuven.be
Wolfgang StammerTechnical University DarmstadtVerified email at cs.tu-darmstadt.de
Emanuele MarconatoUniversity of Pisa and University of TrentoVerified email at unitn.it
Andrea BontempelliUniversity of TrentoVerified email at unitn.it
Guy Van den BroeckProfessor and Samueli Fellow, UCLAVerified email at cs.ucla.edu
Bruno LepriFondazione Bruno Kessler/Ipazia S.p.a.Verified email at fbk.eu
Paolo MorettinAssistant professor (RTD-A), University of TrentoVerified email at unitn.it
Anne-Katrin MahleinInstitute of Sugar Beet Research, GöttingenVerified email at ifz-goettingen.de
Patrick SchramowskiTU DarmstadtVerified email at cs.tu-darmstadt.de
qiang shenPh.D student of computer scienceVerified email at mails.jlu.edu.cn
YooJung ChoiAssistant Professor, Arizona State UniversityVerified email at asu.edu
Anji LiuPh.D. Student of Computer Science, UCLAVerified email at cs.ucla.edu
Xiaoting ShaoTU DarmstadtVerified email at cs.tu-darmstadt.de

Stefano Teso

Senior Assistant Professor, University of Trento

Verified email at unitn.it

Machine Learning Explainable AI Interactive Machine Learning Neuro-Symbolic AI Constraints


Title Sort by citations Sort by year Sort by title	Cited by Cited by	Year
Explanatory interactive machine learning S Teso, K Kersting Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 239-245, 2019	250	2019
Making deep neural networks right for the right scientific reasons by interacting with their explanations P Schramowski, W Stammer, S Teso, A Brugger, F Herbert, X Shao, ... Nature Machine Intelligence 2 (8), 476-486, 2020	249	2020
Learning constraints from examples L De Raedt, A Passerini, S Teso Thirty-Second AAAI Conference on Artificial Intelligence, 2018	97	2018
Semantic probabilistic layers for neuro-symbolic learning K Ahmed, S Teso, KW Chang, G Van den Broeck, A Vergari Advances in Neural Information Processing Systems 35, 29944-29959, 2022	75	2022
A Compositional Atlas of Tractable Circuit Operations: From Simple Transformations to Complex Information-Theoretic Queries A Vergari, YJ Choi, A Liu, S Teso, GV Broeck Advances in Neural Information Processing Systems 34, 2021	63*	2021
Learning SMT (LRA) constraints using SMT solvers S Kolb, S Teso, A Passerini, L De Raedt Proceedings of the Twenty-Seventh International Joint Conference on …, 2018	53	2018
Structured learning modulo theories S Teso, R Sebastiani, A Passerini Artificial Intelligence 244, 166-187, 2017	51	2017
Leveraging explanations in interactive machine learning: An overview S Teso, Ö Alkan, W Stammer, E Daly Frontiers in Artificial Intelligence 6, 2023	50	2023
Glancenets: Interpretable, leak-proof concept-based models E Marconato, A Passerini, S Teso Advances in Neural Information Processing Systems 35, 21212-21227, 2022	49	2022
Interactive label cleaning with example-based explanations S Teso, A Bontempelli, F Giunchiglia, A Passerini Advances in Neural Information Processing Systems 34, 2021	39	2021
Constructive preference elicitation by setwise max-margin learning S Teso, A Passerini, P Viappiani arXiv preprint arXiv:1604.06020, 2016	38	2016
Concept-level Debugging of Part-Prototype Networks A Bontempelli, S Teso, F Giunchiglia, A Passerini arXiv preprint arXiv:2205.15769, 2022	35	2022
Efficient Generation of Structured Objects with Constrained Adversarial Networks L Di Liello, P Ardino, J Gobbi, P Morettin, S Teso, A Passerini Advances in Neural Information Processing Systems 33, 2020	34*	2020
Putting human behavior predictability in context W Zhang, Q Shen, S Teso, B Lepri, A Passerini, I Bison, F Giunchiglia EPJ Data Science 10 (1), 42, 2021	30	2021
Constructive preference elicitation P Dragone, S Teso, A Passerini Frontiers in Robotics and AI 4, 71, 2018	25	2018
Toward Faithful Explanatory Active Learning with Self-explainable Neural Nets S Teso Proceedings of the Workshop on Interactive Adaptive Learning (IAL 2019), 4-16, 2019	22	2019
Coactive critiquing: Elicitation of preferences and features S Teso, P Dragone, A Passerini Thirty-First AAAI Conference on Artificial Intelligence, 2017	22	2017
Improved multi-level protein–protein interaction prediction with semantic-based regularization C Sacca, S Teso, M Diligenti, A Passerini BMC bioinformatics 15 (1), 103, 2014	21	2014
Constructive preference elicitation over hybrid combinatorial spaces P Dragone, S Teso, A Passerini Thirty-Second AAAI Conference on Artificial Intelligence, 2018	20	2018
Investigating the association between social interactions and personality states dynamics D Gundogdu, AN Finnerty, J Staiano, S Teso, A Passerini, F Pianesi, ... Royal Society open science 4 (9), 170194, 2017	20	2017

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