David Vigouroux

24 papers A* 6A 1Misc 1Journal 13Unranked 3

Year	Rank	Type	Title / Venue / Authors
2026	J	`jnl`	Discovering Data Manifold Geometry via Non-Contracting Flows. CoRR David Vigouroux, Lucas Drumetz, Ronan Fablet, François Rousseau
2025	A*	`conf`	Deep Sturm-Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions. ICML David Vigouroux, Joseba Dalmau, Louis Béthune, Victor Boutin
2025	J	`jnl`	Deep Sturm-Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions. CoRR David Vigouroux, Joseba Dalmau, Louis Béthune, Victor Boutin
2025	J	`jnl`	Follow the Energy, Find the Path: Riemannian Metrics from Energy-Based Models. CoRR Louis Béthune, David Vigouroux, Yilun Du, Rufin VanRullen, Thomas Serre, Victor Boutin
2024	A*	`conf`	DP-SGD Without Clipping: The Lipschitz Neural Network Way. ICLR Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux
2024	J	`jnl`	How to design a dataset compliant with an ML-based system ODD? CoRR Cyril Cappi, Noémie Cohen, Mélanie Ducoffe, Christophe Gabreau, Laurent Gardes, Adrien Gauffriau, Jean-Brice Ginestet, Franck Mamalet, Vincent Mussot, Claire Pagetti, David Vigouroux
2024	—	`conf`	Influenciæ: A Library for Tracing the Influence Back to the Data-Points. xAI (4) Agustin M. Picard, Lucas Hervier, Thomas Fel, David Vigouroux
2023	A*	`conf`	CRAFT: Concept Recursive Activation FacTorization for Explainability. CVPR Thomas Fel, Agustin Martin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre
2023	J	`jnl`	DP-SGD Without Clipping: The Lipschitz Neural Network Way. CoRR Louis Béthune, Thomas Massena, Thibaut Boissin, Yannick Prudent, Corentin Friedrich, Franck Mamalet, Aurélien Bellet, Mathieu Serrurier, David Vigouroux
2023	A*	`conf`	Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. CVPR Thomas Fel, Melanie Ducoffe, David Vigouroux, Rémi Cadène, Mikael Capelle, Claire Nicodème, Thomas Serre
2023	—	`conf`	PUNCC: a Python Library for Predictive Uncertainty Calibration and Conformalization. COPA Mouhcine Mendil, Luca Mossina, David Vigouroux
2022	J	`jnl`	CRAFT: Concept Recursive Activation FacTorization for Explainability. CoRR Thomas Fel, Agustin Martin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre
2022	J	`jnl`	Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. CoRR Thomas Fel, Melanie Ducoffe, David Vigouroux, Rémi Cadène, Mikael Capelle, Claire Nicodeme, Thomas Serre
2022	Misc	`conf`	Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning. SEC Thomas Mullor, David Vigouroux, Louis Béthune
2022	J	`jnl`	Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning. CoRR Thomas Mullor, David Vigouroux, Louis Béthune
2022	A	`conf`	How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks. WACV Thomas Fel, David Vigouroux, Rémi Cadène, Thomas Serre
2022	A*	`conf`	Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. NeurIPS Paul Novello, Thomas Fel, David Vigouroux
2022	J	`jnl`	Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. CoRR Paul Novello, Thomas Fel, David Vigouroux
2022	—	`conf`	Object Detection with Probabilistic Guarantees: A Conformal Prediction Approach. SAFECOMP Workshops Florence de Grancey, Jean-Luc Adam, Lucian Alecu, Sébastien Gerchinovitz, Franck Mamalet, David Vigouroux
2022	J	`jnl`	Xplique: A Deep Learning Explainability Toolbox. CoRR 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, Laurent Gardes, Grégory Flandin, Thomas Serre
2021	A*	`conf`	Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. NeurIPS Thomas Fel, Rémi Cadène, Mathieu Chalvidal, Matthieu Cord, David Vigouroux, Thomas Serre
2021	J	`jnl`	Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. CoRR Thomas Fel, Rémi Cadène, Mathieu Chalvidal, Matthieu Cord, David Vigouroux, Thomas Serre
2020	J	`jnl`	Representativity and Consistency Measures for Deep Neural Network Explanations. CoRR Thomas Fel, David Vigouroux
2018	J	`jnl`	FUNN: Flexible Unsupervised Neural Network. CoRR David Vigouroux, Sylvain Picard