
Louis Béthune
14
Documents
Publications
Publications
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DP-SGD Without Clipping: The Lipschitz Neural Network WayICLR 2024 - 12th International Conference on Learning Representations, 2024, Vienna (Austria), Austria
Communication dans un congrès
hal-04610647
v1
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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-03693355
v3
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A Holistic Approach to Unifying Automatic Concept Extraction and Concept Importance EstimationConference on Neural Information Processing Systems (NeurIPS), 2023, Dec 2023, New Orleans (Louisiana), United States
Communication dans un congrès
hal-04391647
v1
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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-03977272
v2
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Efficient circuit implementation for coined quantum walks on binary trees and application to reinforcement learningACM/IEEE International Workshop on Quantum Computing @ 7th Symposium on Edge Computing (SEC 2022), Dec 2022, Seattle, United States. pp.436-443, ⟨10.1109/SEC54971.2022.00066⟩
Communication dans un congrès
hal-03812297
v2
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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-04049806
v1
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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-03872080
v1
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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-03696248
v1
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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-03981114
v1
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Deep learning with Lipschitz constraintsArtificial Intelligence [cs.AI]. Université de Toulouse, 2024. English. ⟨NNT : 2024TLSES014⟩
Thèse
tel-04674274
v1
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Deep Sturm–Liouville: From Sample-Based to 1D Regularization with Learnable Orthogonal Basis Functions2025
Pré-publication, Document de travail
hal-04446268
v2
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GAN Estimation of Lipschitz Optimal Transport Maps2022
Pré-publication, Document de travail
hal-03575178
v1
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Predicting the Generalization Ability of a Few-Shot ClassifierInformation, 2021, 12 (1), pp.29. ⟨10.3390/info12010029⟩
Article dans une revue
hal-03241656
v1
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Hierarchical and Unsupervised Graph Representation Learning with Loukas’s CoarseningAlgorithms, 2020, 13 (9), pp.206. ⟨10.3390/a13090206⟩
Article dans une revue
hal-02955666
v1
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