Louis Béthune
12
Documents
Publications
|
Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks40th International Conference on Machine Learning, Jul 2023, Honolulu, Hawaii, United States. pp.2245-2271, ⟨10.5555/3618408.3618504⟩
Communication dans un congrès
hal-03977272v2
|
|
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport PerspectiveConference on Neural Information Processing Systems (NeurIPS), Neural Information Processing Systems Foundation, Dec 2023, New Orleans (Louisiana), United States
Communication dans un congrès
hal-03693355v3
|
Gaussian Processes on Distributions based on Regularized Optimal Transport26th International Conference on Artificial Intelligence and Statistics (AISTATS 2023), Apr 2023, Valencia, Spain. ⟨10.48550/arXiv.2210.06574⟩
Communication dans un congrès
hal-03981114v1
|
|
|
CRAFT: Concept Recursive Activation FacTorization for ExplainabilityProceedings of the IEEE / CVF Computer Vision and Pattern Recognition Conference (CVPR), 2023., 2023, Vancouver, Canada
Communication dans un congrès
hal-04049806v1
|
|
Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learningACM/IEEE International Workshop on Quantum Computing, Dec 2022, Seattle, United States
Communication dans un congrès
hal-03812297v2
|
Pay attention to your loss: understanding misconceptions about 1-Lipschitz neural networksAdvances in Neural Information Processing Systems, Nov 2022, New Orleans, United States. ⟨10.48550/arXiv.2104.05097⟩
Communication dans un congrès
hal-03872080v1
|
|
Xplique: A Deep Learning Explainability ToolboxThe Conference on Computer Vision and Pattern Recognition, Workshop: Explainable Artificial Intelligence for Computer Vision (XAI4CV), Jun 2022, Nouvelle-Orléans, United States
Communication dans un congrès
hal-03696248v1
|
|
Predicting the Generalization Ability of a Few-Shot ClassifierInformation, 2021, 12 (1), pp.29. ⟨10.3390/info12010029⟩
Article dans une revue
hal-03241656v1
|
Hierarchical and Unsupervised Graph Representation Learning with Loukas’s CoarseningAlgorithms, 2020, 13 (9), pp.206. ⟨10.3390/a13090206⟩
Article dans une revue
hal-02955666v1
|
|
Deep Sturm–Liouville: Learnable orthogonal basis functions parameterized by neural networks2024
Pré-publication, Document de travail
hal-04446268v1
|
|
DP-SGD Without Clipping: The Lipschitz Neural Network Way2023
Pré-publication, Document de travail
hal-04130913v1
|
|
GAN Estimation of Lipschitz Optimal Transport Maps2022
Pré-publication, Document de travail
hal-03575178v1
|