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Stefano Teso
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Cited by
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Explanatory interactive machine learning
S Teso, K Kersting
Proceedings of the 2019 AAAI/ACM Conference on AI, Ethics, and Society, 239-245, 2019
2092019
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
2022020
Learning constraints from examples
L De Raedt, A Passerini, S Teso
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
832018
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
53*2021
Structured learning modulo theories
S Teso, R Sebastiani, A Passerini
Artificial Intelligence 244, 166-187, 2017
482017
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
452018
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
412022
Constructive preference elicitation by setwise max-margin learning
S Teso, A Passerini, P Viappiani
arXiv preprint arXiv:1604.06020, 2016
362016
Leveraging explanations in interactive machine learning: An overview
S Teso, Ö Alkan, W Stammer, E Daly
Frontiers in Artificial Intelligence 6, 2023
342023
Interactive label cleaning with example-based explanations
S Teso, A Bontempelli, F Giunchiglia, A Passerini
Advances in Neural Information Processing Systems 34, 2021
312021
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
29*2020
Glancenets: Interpretable, leak-proof concept-based models
E Marconato, A Passerini, S Teso
Advances in Neural Information Processing Systems 35, 21212-21227, 2022
272022
Concept-level Debugging of Part-Prototype Networks
A Bontempelli, S Teso, F Giunchiglia, A Passerini
arXiv preprint arXiv:2205.15769, 2022
252022
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
232021
Constructive preference elicitation
P Dragone, S Teso, A Passerini
Frontiers in Robotics and AI 4, 71, 2018
232018
Coactive critiquing: Elicitation of preferences and features
S Teso, P Dragone, A Passerini
Thirty-First AAAI Conference on Artificial Intelligence, 2017
222017
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
202019
Constructive preference elicitation over hybrid combinatorial spaces
P Dragone, S Teso, A Passerini
Thirty-Second AAAI Conference on Artificial Intelligence, 2018
202018
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
202014
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
192017
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