Louis Béthune

According to our database, Louis Béthune authored at least 17 papers between 2020 and 2023.

Collaborative distances:

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

2023

TaCo: Targeted Concept Removal in Output Embeddings for NLP via Information Theory and Explainability.

Fanny Jourdan, Louis Béthune, Agustin Picard, Laurent Risser, Nicholas Asher

CoRR, 2023

DP-SGD Without Clipping: The Lipschitz Neural Network Way.

Louis Béthune, Thomas Massena, Thibaut Boissin, Yannick Prudent, Corentin Friedrich, Franck Mamalet, Aurélien Bellet, Mathieu Serrurier, David Vigouroux

CoRR, 2023

On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective.

Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation.

Thomas Fel, Victor Boutin, Louis Béthune, Rémi Cadène, Mazda Moayeri, Léo Andéol, Mathieu Chalvidal, Thomas Serre

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks.

Louis Béthune, Paul Novello, Guillaume Coiffier, Thibaut Boissin, Mathieu Serrurier, Quentin Vincenot, Andres Troya-Galvis

Proceedings of the International Conference on Machine Learning, 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

Gaussian Processes on Distributions based on Regularized Optimal Transport.

François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes

Proceedings of the International Conference on Artificial Intelligence and Statistics, 2023

2022

When adversarial attacks become interpretable counterfactual explanations.

Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin

CoRR, 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

GAN Estimation of Lipschitz Optimal Transport Maps.

Alberto González-Sanz, Lucas de Lara, Louis Béthune, Jean-Michel Loubes

CoRR, 2022

Pay attention to your loss : understanding misconceptions about Lipschitz neural networks.

Louis Béthune, Thibaut Boissin, Mathieu Serrurier, Franck Mamalet, Corentin Friedrich, Alberto González-Sanz

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

Predicting the Generalization Ability of a Few-Shot Classifier.

Myriam Bontonou, Louis Béthune, Vincent Gripon

Inf., 2021

The Many Faces of 1-Lipschitz Neural Networks.

Louis Béthune, Alberto González-Sanz, Franck Mamalet, Mathieu Serrurier

CoRR, 2021

2020

Ranking Deep Learning Generalization using Label Variation in Latent Geometry Graphs.

Carlos Lassance, Louis Béthune, Myriam Bontonou, Mounia Hamidouche, Vincent Gripon

CoRR, 2020

Predicting the Accuracy of a Few-Shot Classifier.

Myriam Bontonou, Louis Béthune, Vincent Gripon

CoRR, 2020

Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening.

Louis Béthune, Yacouba Kaloga, Pierre Borgnat, Aurélien Garivier, Amaury Habrard

Algorithms, 2020