Vigouroux, David

8 publications

ICML 2025 Deep Sturm–Liouville: From Sample-Based to 1d Regularization with Learnable Orthogonal Basis Functions David Vigouroux, Joseba Dalmau, Louis Béthune, Victor Boutin

NeurIPS 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

ICLR 2024 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

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

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

WACV 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

NeurIPS 2022 Making Sense of Dependence: Efficient Black-Box Explanations Using Dependence Measure Paul Novello, Thomas Fel, David Vigouroux

NeurIPS 2021 Look at the Variance! Efficient Black-Box Explanations with Sobol-Based Sensitivity Analysis Thomas Fel, Remi Cadene, Mathieu Chalvidal, Matthieu Cord, David Vigouroux, Thomas Serre