Papers
[7]
Non-Vacuous Generalization Bounds: Can Rescaling Invariances Help?
Damien Rouchouse*, Antoine Gonon*, Rémi Gribonval, Benjamin Guedj• arXiv• 2025
[6]
Symmetry-Aware Bayesian Optimization via Max Kernels
Anthony Bardou, Antoine Gonon, Aryan Ahadinia, Patrick Thiran• arXiv• 2025
[5]
A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval• ICML 2025
[4]
Fast Inference with Kronecker-Sparse Matrices
Antoine Gonon*, Léon Zheng*, Pascal Carrivain*, Quoc-Tung Le• ICML 2025
[3]
A Path-Norm Toolkit for Modern Networks: Consequences, Promises and Challenges
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval• ICLR 2024 (Spotlight)
[2]
Can Sparsity Improve the Privacy of Neural Networks?
Antoine Gonon*, Léon Zheng*, Clément Lalanne, Quoc-Tung Le, Guillaume Lauga, Can Pouliquen• GRETSI 2023
[1]
Approximation speed of quantized vs. unquantized ReLU neural networks and beyond
Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval• IEEE Transactions on Information Theory• 2023
Thesis
PhD Manuscript Harnessing Symmetries for Modern Deep Learning Challenges: A Path-Lifting Perspective
Antoine Gonon• ENS Lyon• 2024
* = equal contribution