Thibaut Boissin

According to our database, Thibaut Boissin authored at least 17 papers between 2021 and 2026.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2026

Orthogonium : A Unified, Efficient Library of Orthogonal and 1-Lipschitz Building Blocks.

Thibaut Boissin, Franck Mamalet, Valentin Lafargue, Mathieu Serrurier

CoRR, January, 2026

2025

Back to the Baseline: Examining Baseline Effects on Explainability Metrics.

Agustin Martin Picard, Thibaut Boissin, Varshini Subhash, Rémi Cadène, Thomas Fel

CoRR, December, 2025

Turbo-Muon: Accelerating Orthogonality-Based Optimization with Pre-Conditioning.

Thibaut Boissin, Thomas Massena, Franck Mamalet, Mathieu Serrurier

CoRR, December, 2025

Efficient Robust Conformal Prediction via Lipschitz-Bounded Networks.

Thomas Massena, Léo Andéol, Thibaut Boissin, Franck Mamalet, Corentin Friedrich, Mathieu Serrurier, Sébastien Gerchinovitz

Proceedings of the Forty-second International Conference on Machine Learning, 2025

An Adaptive Orthogonal Convolution Scheme for Efficient and Flexible CNN Architectures.

Thibaut Boissin, Franck Mamalet, Thomas Fel, Agustin Martin Picard, Thomas Massena, Mathieu Serrurier

Proceedings of the Forty-second International Conference on Machine Learning, 2025

2024

Fairness seen as global sensitivity analysis.

Clément Benesse, Fabrice Gamboa, Jean-Michel Loubes, Thibaut Boissin

Mach. Learn., May, 2024

DP-SGD Without Clipping: The Lipschitz Neural Network Way.

Louis Béthune, Thomas Massena, Thibaut Boissin, Aurélien Bellet, Franck Mamalet, Yannick Prudent, Corentin Friedrich, Mathieu Serrurier, David Vigouroux

Proceedings of the Twelfth International Conference on Learning Representations, 2024

2023

Unlocking Feature Visualization for Deeper Networks with MAgnitude Constrained Optimization.

Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin Martin Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Laurent Gardes, Thomas Serre

CoRR, 2023

Adversarial alignment: Breaking the trade-off between the strength of an attack and its relevance to human perception.

Drew Linsley, Pinyuan Feng, Thibaut Boissin, Alekh Karkada Ashok, Thomas Fel, Stephanie Olaiya, Thomas Serre

CoRR, 2023

On the explainable properties of 1-Lipschitz Neural Networks: An Optimal Transport Perspective.

Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Unlocking Feature Visualization for Deep Network with MAgnitude Constrained Optimization.

Thomas Fel, Thibaut Boissin, Victor Boutin, Agustin M. Picard, Paul Novello, Julien Colin, Drew Linsley, Tom Rousseau, Rémi Cadène, Lore Goetschalckx, Laurent Gardes, Thomas Serre

Proceedings of the Advances in Neural Information Processing Systems 36: Annual Conference on Neural Information Processing Systems 2023, 2023

Robust One-Class Classification with Signed Distance Function using 1-Lipschitz Neural Networks.

Louis Béthune, Paul Novello, Guillaume Coiffier, Thibaut Boissin, Mathieu Serrurier, Quentin Vincenot, Andres Troya-Galvis

Proceedings of the International Conference on Machine Learning, 2023

CRAFT: Concept Recursive Activation FacTorization for Explainability.

Thomas Fel, Agustin Martin Picard, Louis Béthune, Thibaut Boissin, David Vigouroux, Julien Colin, Rémi Cadène, Thomas Serre

Proceedings of the IEEE/CVF Conference on Computer Vision and Pattern Recognition, 2023

2022

When adversarial attacks become interpretable counterfactual explanations.

Mathieu Serrurier, Franck Mamalet, Thomas Fel, Louis Béthune, Thibaut Boissin

CoRR, 2022

Xplique: A Deep Learning Explainability Toolbox.

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

CoRR, 2022

Pay attention to your loss : understanding misconceptions about Lipschitz neural networks.

Louis Béthune, Thibaut Boissin, Mathieu Serrurier, Franck Mamalet, Corentin Friedrich, Alberto González-Sanz

Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

2021

Achieving Robustness in Classification Using Optimal Transport With Hinge Regularization.

Mathieu Serrurier, Franck Mamalet, Alberto González-Sanz, Thibaut Boissin, Jean-Michel Loubes, Eustasio del Barrio

Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition, 2021