FUNN: Flexible Unsupervised Neural Network. - David Vigouroux; Sylvain Picard (CoRR, 2018)

Representativity and Consistency Measures for Deep Neural Network Explanations. - Thomas Fel; David Vigouroux (CoRR, 2020)

Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. - Thomas Fel; Rémi Cadène; Mathieu Chalvidal; Matthieu Cord; David Vigouroux; Thomas Serre (NeurIPS, 2021)

Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning. - Thomas Mullor; David Vigouroux; Louis Béthune (SEC, 2022)

Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. - Paul Novello; Thomas Fel; David Vigouroux (NeurIPS, 2022)

Object Detection with Probabilistic Guarantees: A Conformal Prediction Approach. - Florence de Grancey; Jean-Luc Adam; Lucian Alecu; Sébastien Gerchinovitz; Franck Mamalet; David Vigouroux (SAFECOMP Workshops, 2022)

How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks. - Thomas Fel; David Vigouroux; Rémi Cadène; Thomas Serre (WACV, 2022)

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)

PUNCC: a Python Library for Predictive Uncertainty Calibration and Conformalization. - Mouhcine Mendil; Luca Mossina; David Vigouroux (COPA, 2023)

Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. - Thomas Fel; Melanie Ducoffe; David Vigouroux; Rémi Cadène; Mikael Capelle; Claire Nicodème; Thomas Serre (CVPR, 2023)

CRAFT: Concept Recursive Activation FacTorization for Explainability. - Thomas Fel; Agustin Martin Picard; Louis Béthune; Thibaut Boissin; David Vigouroux; Julien Colin; Rémi Cadène; Thomas Serre (CVPR, 2023)

DP-SGD Without Clipping: The Lipschitz Neural Network Way. - Louis Béthune; Thomas Massena; Thibaut Boissin; Aurélien Bellet; Franck Mamalet; Yannick Prudent; Corentin Friedrich; Mathieu Serrurier; David Vigouroux (ICLR, 2024)

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

How to design a dataset compliant with an ML-based system ODD? - Cyril Cappi; Noémie Cohen; Mélanie Ducoffe; Christophe Gabreau; Laurent Gardes; Adrien Gauffriau; Jean-Brice Ginestet; Franck Mamalet; Vincent Mussot; Claire Pagetti; David Vigouroux (CoRR, 2024)

Deep Sturm-Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions. - David Vigouroux; Joseba Dalmau; Louis Béthune; Victor Boutin (CoRR, 2025)

Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models. - Louis Béthune; David Vigouroux; Yilun Du; Rufin VanRullen; Thomas Serre; Victor Boutin (CoRR, 2025)