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Louis Béthune
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Journal Articles
- 2024
- [j3]Guillaume Coiffier, Louis Béthune:
1-Lipschitz Neural Distance Fields. Comput. Graph. Forum 43(5): i-x (2024) - 2021
- [j2]Myriam Bontonou, Louis Béthune, Vincent Gripon:
Predicting the Generalization Ability of a Few-Shot Classifier. Inf. 12(1): 29 (2021) - 2020
- [j1]Louis Béthune, Yacouba Kaloga, Pierre Borgnat, Aurélien Garivier, Amaury Habrard:
Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening. Algorithms 13(9): 206 (2020)
Conference and Workshop Papers
- 2024
- [c8]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 - 2023
- [c7]François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes:
Gaussian Processes on Distributions based on Regularized Optimal Transport. AISTATS 2023: 4986-5010 - [c6]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 - [c5]Louis Béthune, Paul Novello, Guillaume Coiffier, Thibaut Boissin, Mathieu Serrurier, Quentin Vincenot, Andres Troya-Galvis:
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks. ICML 2023: 2245-2271 - [c4]Thomas Fel, Victor Boutin, Louis Béthune, Rémi Cadène, Mazda Moayeri, Léo Andéol, Mathieu Chalvidal, Thomas Serre:
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation. NeurIPS 2023 - [c3]Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin:
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective. NeurIPS 2023 - 2022
- [c2]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 - [c1]Louis Béthune, Thibaut Boissin, Mathieu Serrurier, Franck Mamalet, Corentin Friedrich, Alberto González-Sanz:
Pay attention to your loss : understanding misconceptions about Lipschitz neural networks. NeurIPS 2022
Informal and Other Publications
- 2024
- [i17]Thomas Fel, Louis Béthune, Andrew Kyle Lampinen, Thomas Serre, Katherine L. Hermann:
Understanding Visual Feature Reliance through the Lens of Complexity. CoRR abs/2407.06076 (2024) - [i16]Yu-Guan Hsieh, Cheng-Yu Hsieh, Shih-Ying Yeh, Louis Béthune, Hadipour Ansari, Pavan Kumar Anasosalu Vasu, Chun-Liang Li, Ranjay Krishna, Oncel Tuzel, Marco Cuturi:
Graph-Based Captioning: Enhancing Visual Descriptions by Interconnecting Region Captions. CoRR abs/2407.06723 (2024) - [i15]Guillaume Coiffier, Louis Béthune:
1-Lipschitz Neural Distance Fields. CoRR abs/2407.09505 (2024) - 2023
- [i14]Louis Béthune, Paul Novello, Thibaut Boissin, Guillaume Coiffier, Mathieu Serrurier, Quentin Vincenot, Andres Troya-Galvis:
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks. CoRR abs/2303.01978 (2023) - [i13]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) - [i12]Thomas Fel, Victor Boutin, Mazda Moayeri, Rémi Cadène, Louis Béthune, Léo Andéol, Mathieu Chalvidal, Thomas Serre:
A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance Estimation. CoRR abs/2306.07304 (2023) - [i11]Fanny Jourdan, Louis Béthune, Agustin Picard, Laurent Risser, Nicholas Asher:
TaCo: Targeted Concept Removal in Output Embeddings for NLP via Information Theory and Explainability. CoRR abs/2312.06499 (2023) - 2022
- [i10]Alberto González-Sanz, Lucas de Lara, Louis Béthune, Jean-Michel Loubes:
GAN Estimation of Lipschitz Optimal Transport Maps. CoRR abs/2202.07965 (2022) - [i9]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) - [i8]Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin:
When adversarial attacks become interpretable counterfactual explanations. CoRR abs/2206.06854 (2022) - [i7]François Bachoc, Louis Béthune, Alberto González-Sanz, Jean-Michel Loubes:
Gaussian Processes on Distributions based on Regularized Optimal Transport. CoRR abs/2210.06574 (2022) - [i6]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) - [i5]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
- [i4]Louis Béthune, Alberto González-Sanz, Franck Mamalet, Mathieu Serrurier:
The Many Faces of 1-Lipschitz Neural Networks. CoRR abs/2104.05097 (2021) - 2020
- [i3]Louis Béthune, Yacouba Kaloga, Pierre Borgnat, Aurélien Garivier, Amaury Habrard:
Hierarchical and Unsupervised Graph Representation Learning with Loukas's Coarsening. CoRR abs/2007.03373 (2020) - [i2]Myriam Bontonou, Louis Béthune, Vincent Gripon:
Predicting the Accuracy of a Few-Shot Classifier. CoRR abs/2007.04238 (2020) - [i1]Carlos Lassance, Louis Béthune, Myriam Bontonou, Mounia Hamidouche, Vincent Gripon:
Ranking Deep Learning Generalization using Label Variation in Latent Geometry Graphs. CoRR abs/2011.12737 (2020)
Coauthor Index
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