Moreau, Thomas

24 publications

CVPR 2025 FiRe: Fixed-Points of Restoration Priors for Solving Inverse Problems Matthieu Terris, Ulugbek S. Kamilov, Thomas Moreau

TMLR 2025 SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation on Diverse Modalities Yanis Lalou, Theo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Thomas Moreau, Alexandre Gramfort, Rémi Flamary

AISTATS 2025 UNHaP: Unmixing Noise from Hawkes Processes Virginie Loison, Guillaume Staerman, Thomas Moreau

AISTATS 2024 A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization Mathieu Dagréou, Thomas Moreau, Samuel Vaiter, Pierre Ablin

CVPR 2024 Equivariant Plug-and-Play Image Reconstruction Matthieu Terris, Thomas Moreau, Nelly Pustelnik, Julian Tachella

ICMLW 2024 Unmixing Noise from Hawkes Process to Model Learned Physiological Events Guillaume Staerman, Virginie Loison, Thomas Moreau

ICML 2023 FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau

TMLR 2023 PAVI: Plate-Amortized Variational Inference Louis Rouillard, Alexandre Le Bris, Thomas Moreau, Demian Wassermann

ICML 2023 Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals Clément Bonet, Benoı̂t Malézieux, Alain Rakotomamonjy, Lucas Drumetz, Thomas Moreau, Matthieu Kowalski, Nicolas Courty

NeurIPS 2022 A Framework for Bilevel Optimization That Enables Stochastic and Global Variance Reduction Algorithms Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau

NeurIPS 2022 Benchopt: Reproducible, Efficient and Collaborative Optimization Benchmarks Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupre la Tour, Ghislain Durif, Cassio F. Dantas, Quentin Klopfenstein, Johan Larsson, En Lai, Tanguy Lefort, Benoît Malézieux, Badr Moufad, Binh T. Nguyen, Alain Rakotomamonjy, Zaccharie Ramzi, Joseph Salmon, Samuel Vaiter

ICLR 2022 CADDA: Class-Wise Automatic Differentiable Data Augmentation for EEG Signals Cédric Rommel, Thomas Moreau, Joseph Paillard, Alexandre Gramfort

NeurIPS 2022 Deep Invariant Networks with Differentiable Augmentation Layers Cédric Rommel, Thomas Moreau, Alexandre Gramfort

ICLR 2022 DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals Cédric Allain, Alexandre Gramfort, Thomas Moreau

ICLR 2022 SHINE: SHaring the INverse Estimate from the Forward Pass for Bi-Level Optimization and Implicit Models Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau

ICLR 2022 Understanding Approximate and Unrolled Dictionary Learning for Pattern Recovery Benoît Malézieux, Thomas Moreau, Matthieu Kowalski

NeurIPS 2021 HNPE: Leveraging Global Parameters for Neural Posterior Estimation Pedro Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort

NeurIPS 2020 Learning to Solve TV Regularised Problems with Unrolled Algorithms Hamza Cherkaoui, Jeremias Sulam, Thomas Moreau

NeurIPS 2020 NeuMiss Networks: Differentiable Programming for Supervised Learning with Missing Values. Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gael Varoquaux

ICML 2020 Super-Efficiency of Automatic Differentiation for Functions Defined as a Minimum Pierre Ablin, Gabriel Peyré, Thomas Moreau

NeurIPS 2019 Learning Step Sizes for Unfolded Sparse Coding Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort

ICML 2018 DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding Thomas Moreau, Laurent Oudre, Nicolas Vayatis

NeurIPS 2018 Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals Tom Dupré la Tour, Thomas Moreau, Mainak Jas, Alexandre Gramfort

ICLR 2017 Understanding Trainable Sparse Coding with Matrix Factorization Thomas Moreau, Joan Bruna