Gribonval, Remi

25 publications

ICML 2025 A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval

MLJ 2025 Pasco (PArallel Structured COarsening): An Overlay to Speed up Graph Clustering Algorithms Etienne Lasalle, Rémi Vaudaine, Titouan Vayer, Pierre Borgnat, Paulo Gonçalves, Rémi Gribonval, Márton Karsai

ICML 2025 Transformative or Conservative? Conservation Laws for ResNets and Transformers Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré

ICLR 2024 A Path-Norm Toolkit for Modern Networks: Consequences, Promises and Challenges Antoine Gonon, Nicolas Brisebarre, Elisa Riccietti, Rémi Gribonval

ICML 2024 Keep the Momentum: Conservation Laws Beyond Euclidean Gradient Flows Sibylle Marcotte, Rémi Gribonval, Gabriel Peyré

JMLR 2024 Revisiting RIP Guarantees for Sketching Operators on Mixture Models Ayoub Belhadji, Rémi Gribonval

TMLR 2024 Sketch and Shift: A Robust Decoder for Compressive Clustering Ayoub Belhadji, Rémi Gribonval

NeurIPS 2023 Abide by the Law and Follow the Flow: Conservation Laws for Gradient Flows Sibylle Marcotte, Remi Gribonval, Gabriel Peyré

TMLR 2023 About the Cost of Central Privacy in Density Estimation Clément Lalanne, Aurélien Garivier, Rémi Gribonval

JMLR 2023 Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning Titouan Vayer, Rémi Gribonval

NeurIPS 2023 Does a Sparse ReLU Network Training Problem Always Admit an Optimum ? Tung Le, Remi Gribonval, Elisa Riccietti

TMLR 2023 On the Statistical Complexity of Estimation and Testing Under Privacy Constraints Clément Lalanne, Aurélien Garivier, Rémi Gribonval

ICML 2023 Private Statistical Estimation of Many Quantiles Clément Lalanne, Aurélien Garivier, Rémi Gribonval

ICLR 2023 Self-Supervised Learning with Rotation-Invariant Kernels Léon Zheng, Gilles Puy, Elisa Riccietti, Patrick Perez, Rémi Gribonval

ICLR 2021 Training with Quantization Noise for Extreme Model Compression Pierre Stock, Angela Fan, Benjamin Graham, Edouard Grave, Rémi Gribonval, Herve Jegou, Armand Joulin

ICLR 2020 And the Bit Goes Down: Revisiting the Quantization of Neural Networks Pierre Stock, Armand Joulin, Rémi Gribonval, Benjamin Graham, Hervé Jégou

ECML-PKDD 2020 Graph Diffusion Wasserstein Distances Amélie Barbe, Marc Sebban, Paulo Gonçalves, Pierre Borgnat, Rémi Gribonval

AISTATS 2020 Learning with Minibatch Wasserstein : Asymptotic and Gradient Properties Kilian Fatras, Younes Zine, Rémi Flamary, Remi Gribonval, Nicolas Courty

NeurIPS 2019 Don't Take It Lightly: Phasing Optical Random Projections with Unknown Operators Sidharth Gupta, Remi Gribonval, Laurent Daudet, Ivan Dokmanić

ICLR 2019 Equi-Normalization of Neural Networks Pierre Stock, Benjamin Graham, Rémi Gribonval, Hervé Jégou

NeurIPS 2018 MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval Helena Peic Tukuljac, Antoine Deleforge, Remi Gribonval

ICCV 2017 SUBIC: A Supervised, Structured Binary Code for Image Search Himalaya Jain, Joaquin Zepeda, Patrick Perez, Remi Gribonval

ECCV 2016 Approximate Search with Quantized Sparse Representations Himalaya Jain, Patrick Pérez, Rémi Gribonval, Joaquin Zepeda, Hervé Jégou

ICML 2016 Compressive Spectral Clustering Nicolas Tremblay, Gilles Puy, Remi Gribonval, Pierre Vandergheynst

NeurIPS 2013 Reconciling "priors" & "priors" Without Prejudice? Remi Gribonval, Pierre Machart