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David Vigouroux
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2020 – today
- 2024
- [c10]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 - [c9]Agustin Picard, Lucas Hervier, Thomas Fel, David Vigouroux:
Influenciæ: A Library for Tracing the Influence Back to the Data-Points. xAI (4) 2024: 193-204 - [i10]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 abs/2406.14027 (2024) - 2023
- [c8]Mouhcine Mendil, Luca Mossina, David Vigouroux:
PUNCC: a Python Library for Predictive Uncertainty Calibration and Conformalization. COPA 2023: 582-601 - [c7]Thomas Fel, Agustin Martin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre:
CRAFT: Concept Recursive Activation FacTorization for Explainability. CVPR 2023: 2711-2721 - [c6]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: 16153-16163 - [i9]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 abs/2305.16202 (2023) - 2022
- [c5]Thomas Mullor, David Vigouroux, Louis Béthune:
Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning. SEC 2022: 436-443 - [c4]Paul Novello, Thomas Fel, David Vigouroux:
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. NeurIPS 2022 - [c3]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: 316-329 - [c2]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: 1565-1575 - [i8]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 abs/2202.07728 (2022) - [i7]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:
Xplique: A Deep Learning Explainability Toolbox. CoRR abs/2206.04394 (2022) - [i6]Paul Novello, Thomas Fel, David Vigouroux:
Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure. CoRR abs/2206.06219 (2022) - [i5]Thomas Mullor, David Vigouroux, Louis Béthune:
Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning. CoRR abs/2210.06784 (2022) - [i4]Thomas Fel, Agustin Martin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre:
CRAFT: Concept Recursive Activation FacTorization for Explainability. CoRR abs/2211.10154 (2022) - 2021
- [c1]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: 26005-26014 - [i3]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 abs/2111.04138 (2021) - 2020
- [i2]Thomas Fel, David Vigouroux:
Representativity and Consistency Measures for Deep Neural Network Explanations. CoRR abs/2009.04521 (2020)
2010 – 2019
- 2018
- [i1]David Vigouroux, Sylvain Picard:
FUNN: Flexible Unsupervised Neural Network. CoRR abs/1811.01749 (2018)
Coauthor Index
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