Xplique: A Deep Learning Explainability Toolbox. - Thomas Fel; Lucas Hervier; David Vigouroux; Antonin Poché; Justin Plakoo; Rémi Cadène; Mathieu Chalvidal; Julien Colin; Thibaut Boissin; Louis Béthune; Agustin Martin Picard; Claire Nicodeme; et al. (CoRR, 2022)

A survey of Identification and mitigation of Machine Learning algorithmic biases in Image Analysis. - Laurent Risser; Agustin Martin Picard; Lucas Hervier; Jean-Michel Loubes (CoRR, 2022)

Natural Example-Based Explainability: A Survey. - Antonin Poché; Lucas Hervier; Mohamed Chafik Bakkay (xAI (2), 2023)

Detecting and Processing Unsuspected Sensitive Variables for Robust Machine Learning. - Laurent Risser; Agustin Martin Picard; Lucas Hervier; Jean-Michel Loubes (Algorithms, 2023)

Influenciæ: A Library for Tracing the Influence Back to the Data-Points. - Agustin Picard; Lucas Hervier; Thomas Fel; David Vigouroux (xAI (4), 2024)