David Vigouroux

According to our database, David Vigouroux authored at least 14 papers between 2018 and 2024.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

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

Influenciæ: A Library for Tracing the Influence Back to the Data-Points.

Agustin Picard, Lucas Hervier, Thomas Fel, David Vigouroux

Proceedings of the Explainable Artificial Intelligence, 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

Proceedings of the Twelfth International Conference on Learning Representations, 2024

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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 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

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

PUNCC: a Python Library for Predictive Uncertainty Calibration and Conformalization.

Mouhcine Mendil, Luca Mossina, David Vigouroux

Proceedings of the Conformal and Probabilistic Prediction with Applications, 2023

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, Laurent Gardes, Grégory Flandin, Thomas Serre

CoRR, 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

Proceedings of the IEEE/CVF Winter Conference on Applications of Computer Vision, 2022

Object Detection with Probabilistic Guarantees: A Conformal Prediction Approach.

Florence de Grancey, Jean-Luc Adam, Lucian Alecu, Sébastien Gerchinovitz, Franck Mamalet, David Vigouroux

Proceedings of the Computer Safety, Reliability, and Security. SAFECOMP 2022 Workshops, 2022

Making Sense of Dependence: Efficient Black-box Explanations Using Dependence Measure.

Paul Novello, Thomas Fel, David Vigouroux

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learning.

Thomas Mullor, David Vigouroux, Louis Béthune

Proceedings of the 7th IEEE/ACM Symposium on Edge Computing, 2022

2021

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

Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020

Representativity and Consistency Measures for Deep Neural Network Explanations.

Thomas Fel, David Vigouroux

CoRR, 2020

2018

FUNN: Flexible Unsupervised Neural Network.

David Vigouroux, Sylvain Picard

CoRR, 2018