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ORCIDThibault Laugel
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2020 – today
- 2024
[j2]Xavier Renard, Thibault Laugel
, Marcin Detyniecki:
Understanding prediction discrepancies in classification. Mach. Learn. 113(10): 7997-8026 (2024)- [c10]Vincent Grari, Thibault Laugel, Tatsunori Hashimoto, Sylvain Lamprier, Marcin Detyniecki:
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing. ICLR 2024 - [i16]Clara Bove, Thibault Laugel, Marie-Jeanne Lesot, Charles Tijus, Marcin Detyniecki:
Why do explanations fail? A typology and discussion on failures in XAI. CoRR abs/2405.13474 (2024) - [i15]Federico Di Gennaro, Thibault Laugel, Vincent Grari, Xavier Renard, Marcin Detyniecki:
Post-processing fairness with minimal changes. CoRR abs/2408.15096 (2024) - 2023
- [j1]Adulam Jeyasothy, Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
A general framework for personalising post hoc explanations through user knowledge integration. Int. J. Approx. Reason. 160: 108944 (2023) - [c9]Thibault Laugel, Adulam Jeyasothy, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Achieving Diversity in Counterfactual Explanations: a Review and Discussion. FAccT 2023: 1859-1869 - [c8]Adulam Jeyasothy, Agnès Rico, Marie-Jeanne Lesot, Christophe Marsala, Thibault Laugel:
Knowledge Integration in XAI with Gödel Integrals. FUZZ 2023: 1-6 - [i14]Natasa Krco, Thibault Laugel, Jean-Michel Loubes, Marcin Detyniecki:
When Mitigating Bias is Unfair: A Comprehensive Study on the Impact of Bias Mitigation Algorithms. CoRR abs/2302.07185 (2023) - [i13]Thibault Laugel, Adulam Jeyasothy, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Achieving Diversity in Counterfactual Explanations: a Review and Discussion. CoRR abs/2305.05840 (2023) - [i12]Vincent Grari, Thibault Laugel, Tatsunori Hashimoto, Sylvain Lamprier, Marcin Detyniecki:
On the Fairness ROAD: Robust Optimization for Adversarial Debiasing. CoRR abs/2310.18413 (2023) - 2022
- [c7]Adulam Jeyasothy, Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Integrating Prior Knowledge in Post-hoc Explanations. IPMU (2) 2022: 707-719 - [c6]Adulam Jeyasothy, Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Intégration de connaissances dans les méthodes d'explications post-hoc. LFA 2022 - [i11]Adulam Jeyasothy, Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Integrating Prior Knowledge in Post-hoc Explanations. CoRR abs/2204.11634 (2022) - 2021
- [c5]Tom Vermeire, Thibault Laugel, Xavier Renard, David Martens, Marcin Detyniecki:
How to Choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice. PKDD/ECML Workshops (1) 2021: 521-533 - [i10]Xavier Renard, Thibault Laugel, Marcin Detyniecki:
Understanding Prediction Discrepancies in Machine Learning Classifiers. CoRR abs/2104.05467 (2021) - [i9]Rafael Poyiadzi, Xavier Renard, Thibault Laugel, Raúl Santos-Rodríguez, Marcin Detyniecki:
On the overlooked issue of defining explanation objectives for local-surrogate explainers. CoRR abs/2106.05810 (2021) - [i8]Rafael Poyiadzi, Xavier Renard, Thibault Laugel, Raúl Santos-Rodríguez, Marcin Detyniecki:
Understanding surrogate explanations: the interplay between complexity, fidelity and coverage. CoRR abs/2107.04309 (2021) - [i7]Tom Vermeire, Thibault Laugel, Xavier Renard, David Martens, Marcin Detyniecki:
How to choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice. CoRR abs/2107.04427 (2021) - 2020
- [b1]Thibault Laugel:
Local Post-hoc Interpretability for Black-box Classifiers. (Interprétabilité Locale Post-hoc des Algorithmes de Classification "Boîtes noires"). Pierre and Marie Curie University, Paris, France, 2020
2010 – 2019
- 2019
- [c4]Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Xavier Renard, Marcin Detyniecki:
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations. IJCAI 2019: 2801-2807 - [c3]Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Xavier Renard, Marcin Detyniecki:
Unjustified Classification Regions and Counterfactual Explanations in Machine Learning. ECML/PKDD (2) 2019: 37-54 - [i6]Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Issues with post-hoc counterfactual explanations: a discussion. CoRR abs/1906.04774 (2019) - [i5]Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Xavier Renard, Marcin Detyniecki:
The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations. CoRR abs/1907.09294 (2019) - [i4]Vincent Ballet, Xavier Renard, Jonathan Aigrain, Thibault Laugel, Pascal Frossard, Marcin Detyniecki:
Imperceptible Adversarial Attacks on Tabular Data. CoRR abs/1911.03274 (2019) - 2018
- [c2]Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Xavier Renard, Marcin Detyniecki:
Comparison-Based Inverse Classification for Interpretability in Machine Learning. IPMU (1) 2018: 100-111 - [c1]Xavier Renard, Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Detecting Potential Local Adversarial Examples for Human-Interpretable Defense. Nemesis/UrbReas/SoGood/IWAISe/GDM@PKDD/ECML 2018: 41-47 - [i3]Thibault Laugel, Xavier Renard, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Defining Locality for Surrogates in Post-hoc Interpretablity. CoRR abs/1806.07498 (2018) - [i2]Xavier Renard, Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Marcin Detyniecki:
Detecting Potential Local Adversarial Examples for Human-Interpretable Defense. CoRR abs/1809.02397 (2018) - 2017
- [i1]Thibault Laugel, Marie-Jeanne Lesot, Christophe Marsala, Xavier Renard, Marcin Detyniecki:
Inverse Classification for Comparison-based Interpretability in Machine Learning. CoRR abs/1712.08443 (2017)
Coauthor Index
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