Thibault Laugel

Orcid: 0000-0002-5921-3225

According to our database¹, Thibault Laugel authored at least 20 papers between 2017 and 2023.

Collaborative distances:

Dijkstra number² of four.
Erdős number³ of four.

Timeline

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In proceedings

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PhD thesis

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On csauthors.net:

Bibliography

2023

A general framework for personalising post hoc explanations through user knowledge integration.

[BibT_eX]

[DOI]

Int. J. Approx. Reason., September, 2023

On the Fairness ROAD: Robust Optimization for Adversarial Debiasing.

[BibT_eX]

[DOI]

CoRR, 2023

When Mitigating Bias is Unfair: A Comprehensive Study on the Impact of Bias Mitigation Algorithms.

[BibT_eX]

[DOI]

CoRR, 2023

Knowledge Integration in XAI with Gödel Integrals.

[BibT_eX]

[DOI]

Proceedings of the IEEE International Conference on Fuzzy Systems, 2023

Achieving Diversity in Counterfactual Explanations: a Review and Discussion.

[BibT_eX]

[DOI]

Proceedings of the 2023 ACM Conference on Fairness, Accountability, and Transparency, 2023

2022

Intégration de connaissances dans les méthodes d'explications post-hoc.

[BibT_eX]

Proceedings of the Rencontres francophones sur la Logique Floue et ses Applications, 2022

Integrating Prior Knowledge in Post-hoc Explanations.

[BibT_eX]

[DOI]

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems, 2022

2021

Understanding surrogate explanations: the interplay between complexity, fidelity and coverage.

[BibT_eX]

[DOI]

Rafael Poyiadzi

Xavier Renard

Thibault Laugel

Raúl Santos-Rodríguez

Marcin Detyniecki

CoRR, 2021

On the overlooked issue of defining explanation objectives for local-surrogate explainers.

[BibT_eX]

[DOI]

Rafael Poyiadzi

Xavier Renard

Thibault Laugel

Raúl Santos-Rodríguez

Marcin Detyniecki

CoRR, 2021

Understanding Prediction Discrepancies in Machine Learning Classifiers.

[BibT_eX]

[DOI]

Xavier Renard

Thibault Laugel

Marcin Detyniecki

CoRR, 2021

How to Choose an Explainability Method? Towards a Methodical Implementation of XAI in Practice.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Principles and Practice of Knowledge Discovery in Databases, 2021

2020

Local Post-hoc Interpretability for Black-box Classifiers. (Interprétabilité Locale Post-hoc des Algorithmes de Classification "Boîtes noires").

[BibT_eX]

[DOI]

Thibault Laugel

PhD thesis, 2020

2019

Imperceptible Adversarial Attacks on Tabular Data.

[BibT_eX]

[DOI]

CoRR, 2019

Issues with post-hoc counterfactual explanations: a discussion.

[BibT_eX]

[DOI]

CoRR, 2019

Unjustified Classification Regions and Counterfactual Explanations in Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Machine Learning and Knowledge Discovery in Databases, 2019

The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations.

[BibT_eX]

[DOI]

Proceedings of the Twenty-Eighth International Joint Conference on Artificial Intelligence, 2019

2018

Defining Locality for Surrogates in Post-hoc Interpretablity.

[BibT_eX]

[DOI]

CoRR, 2018

Detecting Potential Local Adversarial Examples for Human-Interpretable Defense.

[BibT_eX]

[DOI]

Proceedings of the ECML PKDD 2018 Workshops, 2018

Comparison-Based Inverse Classification for Interpretability in Machine Learning.

[BibT_eX]

[DOI]

Proceedings of the Information Processing and Management of Uncertainty in Knowledge-Based Systems. Theory and Foundations, 2018

2017

Inverse Classification for Comparison-based Interpretability in Machine Learning.

[BibT_eX]

[DOI]

CoRR, 2017

Thibault Laugel

Timeline

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