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
Paolo DragoneTwitterVerified email at twitter.com
Samuel KolbKU LeuvenVerified email at kuleuven.be
Kristian KerstingProfessor of AI & Machine Learning, TU Darmstadt, Co-Director of hessian.ai, Germany, CLAIRE & ELLISVerified email at cs.tu-darmstadt.de
Mohit KumarPhD Student, KU LeuvenVerified email at cs.kuleuven.be
Fausto GiunchigliaProfessor of Computer Science, Università di TrentoVerified email at disi.unitn.it
Wolfgang StammerTechnical University DarmstadtVerified email at cs.tu-darmstadt.de
Bruno LepriFondazione Bruno KesslerVerified email at fbk.eu
Andrea BontempelliUniversity of TrentoVerified email at unitn.it
Anne-Katrin MahleinInstitute of Sugar Beet Reserach, GöttingenVerified email at ifz-goettingen.de
Patrick SchramowskiTU DarmstadtVerified email at cs.tu-darmstadt.de
Roberto SebastianiFull Professor in Computer Science, DISI, University of Trento, ItalyVerified email at unitn.it
Antonio VergariLecturer, University of Edinburgh, UKVerified email at ed.ac.uk
Paolo MorettinPost-doctoral researcher, KU LeuvenVerified email at kuleuven.be
Gust VerbruggenPhD student in Artificial Intelligence, KU LeuvenVerified email at cs.kuleuven.be
Guy Van den BroeckAssociate Professor and Samueli Fellow, UCLAVerified email at cs.ucla.edu
Xiaoting ShaoTU DarmstadtVerified email at cs.tu-darmstadt.de
Franziska HerbertPhD Student @ Ruhr University BochumVerified email at ruhr-uni-bochum.de
Jacopo StaianoResearcher at reciTAL.aiVerified email at media.mit.edu

Stefano Teso

Assistant Professor, University of Trento

Verified email at unitn.it

Machine Learning Explainable AI Interactive Machine Learning Constraint Learning Structured-output Prediction


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	108*	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	98*	2020
Learning constraints from examples L De Raedt, A Passerini, S Teso Thirty-Second AAAI Conference on Artificial Intelligence, 2018	59	2018
Structured learning modulo theories S Teso, R Sebastiani, A Passerini Artificial Intelligence 244, 166-187, 2017	45	2017
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	38	2018
Constructive Preference Elicitation by Setwise Max-Margin Learning S Teso, A Passerini, P Viappiani Twenty-Fifth International Joint Conference on Artificial Intelligence …, 2016	32*	2016
Constructive Preference Elicitation by Setwise Max-Margin Learning S Teso, A Passerini, P Viappiani Twenty-Fifth International Joint Conference on Artificial Intelligence …, 2016	32*	2016
Constructive preference elicitation P Dragone, S Teso, A Passerini Frontiers in Robotics and AI 4, 71, 2018	20	2018
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	18	2014
Ego-centric graphlets for personality and affective states recognition S Teso, J Staiano, B Lepri, A Passerini, F Pianesi 2013 International Conference on Social Computing, 874-877, 2013	18	2013
Coactive critiquing: Elicitation of preferences and features S Teso, P Dragone, A Passerini Thirty-First AAAI Conference on Artificial Intelligence, 2017	17	2017
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	16	2017
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	15*	2021
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	15*	2020
Constructive preference elicitation over hybrid combinatorial spaces P Dragone, S Teso, A Passerini Thirty-Second AAAI Conference on Artificial Intelligence, 2018	14	2018
Elements of an Automatic Data Scientist L De Raedt, H Blockeel, S Kolb, S Teso, G Verbruggen International Symposium on Intelligent Data Analysis, 3-14, 2018	12	2018
Machine Guides, Human Supervises: Interactive Learning with Global Explanations T Popordanoska, M Kumar, S Teso arXiv preprint arXiv:2009.09723, 2020	11	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	9	2021
Learning Max-SAT from contextual examples for combinatorial optimisation M Kumar, S Kolb, S Teso, L De Raedt Proceedings of the 34th Conference on Artificial Intelligence (AAAI), 2020	9	2020
Automating Personnel Rostering by Learning Constraints Using Tensors M Kumar, S Teso, P De Causmaecker, L De Raedt 2019 IEEE 31st International Conference on Tools with Artificial …, 2019	9	2019

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