Thibaut Boissin

Publication Activity (10 Years)

Years Active: 2020-2024
Publications (10 Years): 16

Top Topics

Top Venues

Publications

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)
Clément Benesse, Fabrice Gamboa, Jean-Michel Loubes, Thibaut Boissin
Fairness seen as global sensitivity analysis. Mach. Learn. 113 (5) (2024)
Thomas Fel, Agustin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadènc, Thomas Serre
CRAFT: Concept Recursive Activation FacTorization for Explainability. CVPR (2023)
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)
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 (2023)
Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Lore Goetschalckx, Laurent Gardes, Thomas Serre
Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization. NeurIPS (2023)
Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Laurent Gardes, Thomas Serre
Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization. CoRR (2023)
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)
Drew Linsley, Pinyuan Feng, Thibaut Boissin, Alekh Karkada Ashok, Thomas Fel, Stephanie Olaiya, Thomas Serre
Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception. CoRR (2023)
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 (2023)
Thomas Fel, Lucas Hervier, David Vigouroux, Antonin Poche, Justin Plakoo, Rémi Cadène, Mathieu Chalvidal, Julien Colin, Thibaut Boissin, Louis Béthune, Agustin Picard, Claire Nicodeme, Laurent Gardes, Grégory Flandin, Thomas Serre
Xplique: A Deep Learning Explainability Toolbox. CoRR (2022)
Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin
When adversarial attacks become interpretable counterfactual explanations. CoRR (2022)
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)
Thomas Fel, Agustin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre
CRAFT: Concept Recursive Activation FacTorization for Explainability. CoRR (2022)
Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio
Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization. CVPR (2021)
Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio
Achieving robustness in classification using optimal transport with hinge regularization. CoRR (2020)