Remi Gribonval

20 papers · 2013–2025 · 7 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (10) 🧭 Keyword Pioneer 🗺️ Taxonomy Completionist (29) 🌉 Interdisciplinary Bridge 🌈 Renaissance Researcher (6) 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (7) 🏃 Academic Marathon (12) 🏆 Keyword Champion 👑 Triple Crown 🔥 Unstoppable (6) ⚡ Prolific Year (5) 💎 Century Club (20) ❓ The Questioner (3) 📈 Trend Setter 🗃️ Keyword Collector (58)

Conferences

ICLR (5) ICML (5) NIPS (5) JMLR (2) AISTATS (1) CVPR (1) ICCV (1)

Top co-authors

Elisa Riccietti (4) Patrick Pérez (3) Herve Jegou (3) Gabriel Peyré (3) Pierre Stock (3) Benjamin Graham (3) Sibylle Marcotte (3) Joaquin Zepeda (2) Himalaya Jain (2) Gilles Puy (2)

Research topics

Differential Privacy (1)

Keywords

compressive sensing (2) compressed sensing (1) sparse regularization (1) blind source separation (1) convex optimization (1) bayesian inference (1) spectral clustering (1) density estimation (1) optimal transport (1) posterior distribution (1) bayesian estimation (1) probability distribution (1) random sampling (1) blind channel identification (1) differential privacy (1) laplacian matrix (1) statistical estimation (1) maximum mean discrepancy (1) restricted isometry property (1) wasserstein distance (1)

Papers

A Rescaling-Invariant Lipschitz Bound Based on Path-Metrics for Modern ReLU Network Parameterizations ICML 2025

Transformative or Conservative? Conservation laws for ResNets and Transformers ICML 2025

A path-norm toolkit for modern networks: consequences, promises and challenges ICLR 2024

Revisiting RIP Guarantees for Sketching Operators on Mixture Models JMLR 2024

Keep the Momentum: Conservation Laws beyond Euclidean Gradient Flows ICML 2024

Abide by the law and follow the flow: conservation laws for gradient flows NIPS 2023

Controlling Wasserstein Distances by Kernel Norms with Application to Compressive Statistical Learning JMLR 2023

Self-supervised learning with rotation-invariant kernels ICLR 2023

Private Statistical Estimation of Many Quantiles ICML 2023

Does a sparse ReLU network training problem always admit an optimum ? NIPS 2023

Training with Quantization Noise for Extreme Model Compression ICLR 2021

Learning with minibatch Wasserstein : asymptotic and gradient properties AISTATS 2020

And the Bit Goes Down: Revisiting the Quantization of Neural Networks ICLR 2020

Equi-normalization of Neural Networks ICLR 2019

Don't take it lightly: Phasing optical random projections with unknown operators NIPS 2019

MULAN: A Blind and Off-Grid Method for Multichannel Echo Retrieval NIPS 2018

Learning a Complete Image Indexing Pipeline CVPR 2018

SUBIC: A Supervised, Structured Binary Code for Image Search ICCV 2017

Compressive Spectral Clustering ICML 2016

Reconciling "priors" & "priors" without prejudice? NIPS 2013