Thibault Laugel | DeepAI

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∙ 05/10/2023

Achieving Diversity in Counterfactual Explanations: a Review and Discussion

In the field of Explainable Artificial Intelligence (XAI), counterfactua...

0 Thibault Laugel, et al. ∙

∙ 02/14/2023

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

Most works on the fairness of machine learning systems focus on the blin...

0 Natasa Krco, et al. ∙

∙ 04/25/2022

Integrating Prior Knowledge in Post-hoc Explanations

In the field of eXplainable Artificial Intelligence (XAI), post-hoc inte...

6 Adulam Jeyasothy, et al. ∙

∙ 07/09/2021

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

Explainability is becoming an important requirement for organizations th...

36 Tom Vermeire, et al. ∙

∙ 07/09/2021

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

This paper analyses the fundamental ingredients behind surrogate explana...

16 Rafael Poyiadzi, et al. ∙

∙ 06/10/2021

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

Local surrogate approaches for explaining machine learning model predict...

3 Rafael Poyiadzi, et al. ∙

∙ 04/12/2021

Understanding Prediction Discrepancies in Machine Learning Classifiers

A multitude of classifiers can be trained on the same data to achieve si...

18 Xavier Renard, et al. ∙

∙ 11/08/2019

Imperceptible Adversarial Attacks on Tabular Data

Security of machine learning models is a concern as they may face advers...

0 Vincent Ballet, et al. ∙

∙ 07/22/2019

The Dangers of Post-hoc Interpretability: Unjustified Counterfactual Explanations

Post-hoc interpretability approaches have been proven to be powerful too...

0 Thibault Laugel, et al. ∙

∙ 06/11/2019

Issues with post-hoc counterfactual explanations: a discussion

Counterfactual post-hoc interpretability approaches have been proven to ...

0 Thibault Laugel, et al. ∙

∙ 09/07/2018

Detecting Potential Local Adversarial Examples for Human-Interpretable Defense

Machine learning models are increasingly used in the industry to make de...

0 Xavier Renard, et al. ∙

∙ 06/19/2018

Defining Locality for Surrogates in Post-hoc Interpretablity

Local surrogate models, to approximate the local decision boundary of a ...

0 Thibault Laugel, et al. ∙

∙ 12/22/2017

Inverse Classification for Comparison-based Interpretability in Machine Learning

In the context of post-hoc interpretability, this paper addresses the ta...

0 Thibault Laugel, et al. ∙