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Thibaut Boissin
Thibaut Boissin
IRT Saint-Exupéry
Adresse e-mail validée de irt-saintexupery.com
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Achieving robustness in classification using optimal transport with hinge regularization
M Serrurier, F Mamalet, A González-Sanz, T Boissin, JM Loubes, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2021
452021
Craft: Concept recursive activation factorization for explainability
T Fel, A Picard, L Bethune, T Boissin, D Vigouroux, J Colin, R Cadène, ...
Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern …, 2023
412023
Pay attention to your loss: understanding misconceptions about lipschitz neural networks
L Béthune, T Boissin, M Serrurier, F Mamalet, C Friedrich, ...
Advances in Neural Information Processing Systems 35, 20077-20091, 2022
32*2022
Xplique: A deep learning explainability toolbox
T Fel, L Hervier, D Vigouroux, A Poche, J Plakoo, R Cadene, M Chalvidal, ...
arXiv preprint arXiv:2206.04394, 2022
182022
Fairness seen as global sensitivity analysis
C Bénesse, F Gamboa, JM Loubes, T Boissin
Machine Learning, 1-28, 2022
132022
On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective
M Serrurier, F Mamalet, T Fel, L Béthune, T Boissin
Advances in Neural Information Processing Systems 36, 2024
6*2024
Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization
FEL Thomas, T Boissin, V Boutin, AM Picard, P Novello, J Colin, D Linsley, ...
Thirty-seventh Conference on Neural Information Processing Systems, 2023
5*2023
Dp-sgd without clipping: The lipschitz neural network way
L Béthune, T Masséna, T Boissin, Y Prudent, C Friedrich, F Mamalet, ...
arXiv preprint arXiv:2305.16202, 2023
32023
Robust one-class classification with signed distance function using 1-lipschitz neural networks
L Béthune, P Novello, T Boissin, G Coiffier, M Serrurier, Q Vincenot, ...
arXiv preprint arXiv:2303.01978, 2023
32023
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception
D Linsley, P Feng, T Boissin, AK Ashok, T Fel, S Olaiya, T Serre
arXiv preprint arXiv:2306.03229, 2023
12023
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