David Vigouroux

Publication Activity (10 Years)

Years Active: 2018-2024
Publications (10 Years): 19

Top Topics

Sensitivity Analysis

Top Venues

SAFECOMP Workshops

Publications

Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux
DP-SGD Without Clipping: The Lipschitz Neural Network Way. ICLR (2024)
Cyril Cappi, Noémie Cohen, Mélanie Ducoffe, Christophe Gabreau, Laurent Gardes, Adrien Gauffriau, Jean-Brice Ginestet, Franck Mamalet, Vincent Mussot, Claire Pagetti, David Vigouroux
How to design a dataset compliant with an ML-based system ODD? CoRR (2024)
Thomas Fel, Agustin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadènc, Thomas Serre
CRAFT: Concept Recursive Activation FacTorization for Explainability. CVPR (2023)
Louis Béthune, Thomas Massena, Thibaut Boissin, Yannick Prudent, Corentin Friedrich, Franck Mamalet, Aurélien Bellet, Mathieu Serrurier, David Vigouroux
DP-SGD Without Clipping: The Lipschitz Neural Network Way. CoRR (2023)
Mouhcine Mendil, Luca Mossina, David Vigouroux
PUNCC: a Python Library for Predictive Uncertainty Calibration and Conformalization. COPA (2023)
Thomas Fel, Melanie Ducoffe, David Vigouroux, Rémi Cadène, Mikael Capelle, Claire Nicodème, Thomas Serre
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. CVPR (2023)
Paul Novello, Thomas Fel, David Vigouroux
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. CoRR (2022)
Thomas Fel, Melanie Ducoffe, David Vigouroux, Rémi Cadène, Mikael Capelle, Claire Nicodeme, Thomas Serre
Don't Lie to Me! Robust and Efficient Explainability with Verified Perturbation Analysis. CoRR (2022)
Paul Novello, Thomas Fel, David Vigouroux
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. NeurIPS (2022)
Thomas Fel, Lucas Hervier, David Vigouroux, Antonin Poche, Justin Plakoo, Rémi Cadène, Mathieu Chalvidal, Julien Colin, Thibaut Boissin, Louis Béthune, Agustin Picard, Claire Nicodeme, Laurent Gardes, Grégory Flandin, Thomas Serre
Xplique: A Deep Learning Explainability Toolbox. CoRR (2022)
Florence De Grancey, Jean-Luc Adam, Lucian Alecu, Sébastien Gerchinovitz, Franck Mamalet, David Vigouroux
Object Detection with Probabilistic Guarantees: A Conformal Prediction Approach. SAFECOMP Workshops (2022)
Thomas Mullor, David Vigouroux, Louis Béthune
Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning. CoRR (2022)
Thomas Mullor, David Vigouroux, Louis Béthune
Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning. SEC (2022)
Thomas Fel, David Vigouroux, Rémi Cadène, Thomas Serre
How Good is your Explanation? Algorithmic Stability Measures to Assess the Quality of Explanations for Deep Neural Networks. WACV (2022)
Thomas Fel, Agustin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre
CRAFT: Concept Recursive Activation FacTorization for Explainability. CoRR (2022)
Thomas Fel, Rémi Cadène, Mathieu Chalvidal, Matthieu Cord, David Vigouroux, Thomas Serre
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. NeurIPS (2021)
Thomas Fel, Rémi Cadène, Mathieu Chalvidal, Matthieu Cord, David Vigouroux, Thomas Serre
Look at the Variance! Efficient Black-box Explanations with Sobol-based Sensitivity Analysis. CoRR (2021)
Thomas Fel, David Vigouroux
Representativity and Consistency Measures for Deep Neural Network Explanations. CoRR (2020)
David Vigouroux, Sylvain Picard
FUNN: Flexible Unsupervised Neural Network. CoRR (2018)