Thomas Moreau

76 papers A* 18A 2B 1Misc 1Journal 49Unranked 4
YearRankTypeTitle / Venue / Authors
2026 J jnl
Analysis and Synthesis Denoisers for Forward-Backward Plug-and-Play Algorithms.
SIAM J. Imaging Sci.
Matthieu Kowalski, Benoît Malézieux, Thomas Moreau, Audrey Repetti
2025 J jnl
DeepInverse: A Python package for solving imaging inverse problems with deep learning.
J. Open Source Softw.
Julián Tachella, Matthieu Terris, Samuel Hurault, Andrew Wang, Leo Davy, Jérémy Scanvic, Victor Sechaud, Romain Vo, Thomas Moreau, Thomas Davies, Dongdong Chen, Nils Laurent, Brayan Monroy, Jonathan Dong, Zhiyuan Hu, Minh-Hai Nguyen, Florian Sarron, Pierre Weiss, Paul Escande, Mathurin Massias, Thibaut Modrzyk, Brett Levac, Tobías I. Liaudat, Maxime Song, Johannes Hertrich, Sebastian Neumayer, Georg Schramm
2025 A* conf
FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems.
CVPR
Matthieu Terris, Ulugbek S. Kamilov, Thomas Moreau
2025 J jnl
From Denoising Score Matching to Langevin Sampling: A Fine-Grained Error Analysis in the Gaussian Setting.
CoRR
Samuel Hurault, Matthieu Terris, Thomas Moreau, Gabriel Peyré
2025 B conf
Numerically Efficient Parametric Inference for Learning Space-Time Hawkes Processes.
DSAA
Emilia Siviero, Guillaume Staerman, Stéphan Clémençon, Thomas Moreau
2025 J jnl
RoseCDL: Robust and Scalable Convolutional Dictionary Learning for Rare-event Detection.
CoRR
Jad Yehya, Mansour Benbakoura, Cédric Allain, Benoît Malézieux, Matthieu Kowalski, Thomas Moreau
2025 J jnl
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation On Diverse Modalities.
Trans. Mach. Learn. Res.
Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Ambroise Odonnat, Thomas Moreau, Alexandre Gramfort, Rémi Flamary
2025 J jnl
Simulation-Based Inference: A Practical Guide.
CoRR
Michael Deistler, Jan Boelts, Peter Steinbach, Guy Moss, Thomas Moreau, Manuel Glöckler, Pedro L. C. Rodrigues, Julia Linhart, Janne K. Lappalainen, Benjamin Kurt Miller, Pedro J. Gonçalves, Jan-Matthis Lueckmann, Cornelius Schröder, Jakob H. Macke
2025 A conf
UNHaP: Unmixing Noise from Hawkes Processes.
AISTATS
Virginie Loison, Guillaume Staerman, Thomas Moreau
2025 J jnl
sbi reloaded: a toolkit for simulation-based inference workflows.
J. Open Source Softw.
Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke
2024 A conf
A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization.
AISTATS
Mathieu Dagréou, Thomas Moreau, Samuel Vaiter, Pierre Ablin
2024 J jnl
Analysis and Synthesis Denoisers for Forward-Backward Plug-and-Play Algorithms.
CoRR
Matthieu Kowalski, Benoît Malézieux, Thomas Moreau, Audrey Repetti
2024 J jnl
Convolutional Sparse Coding for Time Series Via a ℓ 0 Penalty: An Efficient Algorithm With Statistical Guarantees.
Stat. Anal. Data Min.
Charles Truong, Thomas Moreau
2024 A* conf
Equivariant Plug-and-Play Image Reconstruction.
CVPR
Matthieu Terris, Thomas Moreau, Nelly Pustelnik, Julián Tachella
2024 J jnl
FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems.
CoRR
Matthieu Terris, Ulugbek S. Kamilov, Thomas Moreau
2024 J jnl
Flexible Parametric Inference for Space-Time Hawkes Processes.
CoRR
Emilia Siviero, Guillaume Staerman, Stéphan Clémençon, Thomas Moreau
2024 J jnl
S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attention.
CoRR
Pierre Guetschel, Thomas Moreau, Michael Tangermann
2024 J jnl
SKADA-Bench: Benchmarking Unsupervised Domain Adaptation Methods with Realistic Validation.
CoRR
Yanis Lalou, Théo Gnassounou, Antoine Collas, Antoine de Mathelin, Oleksii Kachaiev, Ambroise Odonnat, Alexandre Gramfort, Thomas Moreau, Rémi Flamary
2024 J jnl
The largest EEG-based BCI reproducibility study for open science: the MOABB benchmark.
CoRR
Sylvain Chevallier, Igor Carrara, Bruno Aristimunha, Pierre Guetschel, Sara Sedlar, Bruna Lopes, Sébastien Velut, Salim Khazem, Thomas Moreau
2024 J jnl
Unmixing Noise from Hawkes Process to Model Learned Physiological Events.
CoRR
Guillaume Staerman, Virginie Loison, Thomas Moreau
2024 J jnl
sbi reloaded: a toolkit for simulation-based inference workflows.
CoRR
Jan Boelts, Michael Deistler, Manuel Glöckler, Álvaro Tejero-Cantero, Jan-Matthis Lueckmann, Guy Moss, Peter Steinbach, Thomas Moreau, Fabio Muratore, Julia Linhart, Conor Durkan, Julius Vetter, Benjamin Kurt Miller, Maternus Herold, Abolfazl Ziaeemehr, Matthijs Pals, Theo Gruner, Sebastian Bischoff, Nastya Krouglova, Richard Gao, Janne K. Lappalainen, Bálint Mucsányi, Felix Pei, Auguste Schulz, Zinovia Stefanidi, Pedro Rodrigues, Cornelius Schröder, Faried Abu Zaid, Jonas Beck, Jaivardhan Kapoor, David S. Greenberg, Pedro J. Gonçalves, Jakob H. Macke
2023 J jnl
A Near-Optimal Algorithm for Bilevel Empirical Risk Minimization.
CoRR
Mathieu Dagréou, Thomas Moreau, Samuel Vaiter, Pierre Ablin
2023 J jnl
Equivariant plug-and-play image reconstruction.
CoRR
Matthieu Terris, Thomas Moreau, Nelly Pustelnik, Julián Tachella
2023 A* conf
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels.
ICML
Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau
2023 J jnl
Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers.
CoRR
Matthieu Terris, Thomas Moreau
2023 J jnl
PAVI: Plate-Amortized Variational Inference.
CoRR
Louis Rouillard, Alexandre Le Bris, Thomas Moreau, Demian Wassermann
2023 J jnl
PAVI: Plate-Amortized Variational Inference.
Trans. Mach. Learn. Res.
Louis Rouillard, Alexandre Le Bris, Thomas Moreau, Demian Wassermann
2023 A* conf
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals.
ICML
Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy, Lucas Drumetz, Thomas Moreau, Matthieu Kowalski, Nicolas Courty
2023 J jnl
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals.
CoRR
Clément Bonet, Benoît Malézieux, Alain Rakotomamonjy, Lucas Drumetz, Thomas Moreau, Matthieu Kowalski, Nicolas Courty
2023 J jnl
Test like you Train in Implicit Deep Learning.
CoRR
Zaccharie Ramzi, Pierre Ablin, Gabriel Peyré, Thomas Moreau
2023 J jnl
Using convolutional dictionary learning to detect task-related neuromagnetic transients and ageing trends in a large open-access dataset.
NeuroImage
Lindsey Power, Cédric Allain, Thomas Moreau, Alexandre Gramfort, Timothy Bardouille
2023 J jnl
Wavelets in the Deep Learning Era.
J. Math. Imaging Vis.
Zaccharie Ramzi, Kevin Michalewicz, Jean-Luc Starck, Thomas Moreau, Philippe Ciuciu
2022 A* conf
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms.
NeurIPS
Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau
2022 J jnl
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms.
CoRR
Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau
2022 A* conf
Benchopt: Reproducible, efficient and collaborative optimization benchmarks.
NeurIPS
Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio 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
2022 J jnl
Benchopt: Reproducible, efficient and collaborative optimization benchmarks.
CoRR
Thomas Moreau, Mathurin Massias, Alexandre Gramfort, Pierre Ablin, Pierre-Antoine Bannier, Benjamin Charlier, Mathieu Dagréou, Tom Dupré la Tour, Ghislain Durif, Cássio 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
2022 A* conf
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals.
ICLR
Cédric Rommel, Thomas Moreau, Joseph Paillard, Alexandre Gramfort
2022 J jnl
Data augmentation for learning predictive models on EEG: a systematic comparison.
CoRR
Cédric Rommel, Joseph Paillard, Thomas Moreau, Alexandre Gramfort
2022 A* conf
Deep invariant networks with differentiable augmentation layers.
NeurIPS
Cédric Rommel, Thomas Moreau, Alexandre Gramfort
2022 J jnl
Deep invariant networks with differentiable augmentation layers.
CoRR
Cédric Rommel, Thomas Moreau, Alexandre Gramfort
2022 J jnl
DiCoDiLe: Distributed Convolutional Dictionary Learning.
IEEE Trans. Pattern Anal. Mach. Intell.
Thomas Moreau, Alexandre Gramfort
2022 A* conf
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals.
ICLR
Cédric Allain, Alexandre Gramfort, Thomas Moreau
2022 J jnl
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels.
CoRR
Guillaume Staerman, Cédric Allain, Alexandre Gramfort, Thomas Moreau
2022 J jnl
PAVI: Plate-Amortized Variational Inference.
CoRR
Louis Rouillard, Thomas Moreau, Demian Wassermann
2022 A* conf
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models.
ICLR
Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau
2022 A* conf
Understanding approximate and unrolled dictionary learning for pattern recovery.
ICLR
Benoît Malézieux, Thomas Moreau, Matthieu Kowalski
2021 J jnl
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals.
CoRR
Cédric Rommel, Thomas Moreau, Alexandre Gramfort
2021 J jnl
Dictionary and prior learning with unrolled algorithms for unsupervised inverse problems.
CoRR
Benoît Malézieux, Thomas Moreau, Matthieu Kowalski
2021 J jnl
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals.
CoRR
Cédric Allain, Alexandre Gramfort, Thomas Moreau, A. Preprint
2021 A* conf
HNPE: Leveraging Global Parameters for Neural Posterior Estimation.
NeurIPS
Pedro Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort
2021 J jnl
Leveraging Global Parameters for Flow-based Neural Posterior Estimation.
CoRR
Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort
2021 J jnl
Multivariate semi-blind deconvolution of fMRI time series.
NeuroImage
Hamza Cherkaoui, Thomas Moreau, Abderrahim Halimi, Claire Leroy, Philippe Ciuciu
2021 J jnl
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models.
CoRR
Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau
2020 — conf
Extraction of Nystagmus Patterns from Eye-Tracker Data with Convolutional Sparse Coding.
EMBC
Clément Lalanne, Maxence Rateaux, Laurent Oudre, Matthieu P. Robert, Thomas Moreau
2020 J jnl
Extraction of Nystagmus Patterns from Eye-Tracker Data with Convolutional Sparse Coding.
CoRR
Clément Lalanne, Maxence Rateaux, Laurent Oudre, Matthieu P. Robert, Thomas Moreau
2020 J jnl
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.
npj Digit. Medicine
Gabriel A. Brat, Griffin M. Weber, Nils Gehlenborg, Paul Avillach, Nathan P. Palmer, Luca Chiovato, James J. Cimino, Lemuel R. Waitman, Gilbert S. Omenn, Alberto Malovini, Jason H. Moore, Brett K. Beaulieu-Jones, Valentina Tibollo, Shawn N. Murphy, Sehi L'Yi, Mark S. Keller, Riccardo Bellazzi, David A. Hanauer, Arnaud Serret-Larmande, Alba Gutiérrez-Sacristán, John J. Holmes, Douglas S. Bell, Kenneth D. Mandl, Robert W. Follett, Jeffrey G. Klann, Douglas A. Murad, Luigia Scudeller, Mauro Bucalo, Katie G. Kirchoff, Jean B. Craig, Jihad S. Obeid, Vianney Jouhet, Romain Griffier, Sébastien Cossin, Bertrand Moal, Lav P. Patel, Antonio Bellasi, Hans-Ulrich Prokosch, Detlef Kraska, Piotr Sliz, Amelia L. M. Tan, Kee Yuan Ngiam, Alberto Zambelli, Danielle L. Mowery, Emily Schriver, Batsal Devkota, Robert L. Bradford, Mohamad Daniar, Christel Daniel, Vincent Benoit, Romain Bey, Nicolas Paris, Patricia Serre, Nina Orlova, Julien Dubiel, Martin Hilka, Anne-Sophie Jannot, Stéphane Bréant, Judith Leblanc, Nicolas Griffon, Anita Burgun, Mélodie Bernaux, Arnaud Sandrin, Elisa Salamanca, Sylvie Cormont, Thomas Ganslandt, Tobias Gradinger, Julien Champ, Martin Boeker, Patricia Martel, Loic Estève, Alexandre Gramfort, Olivier Grisel, Damien Leprovost, Thomas Moreau, Gaël Varoquaux, Jill-Jênn Vie, Demian Wassermann, Arthur Mensch, Charlotte Caucheteux, Christian Haverkamp, Guillaume Lemaitre, Silvano Bosari, Ian D. Krantz, Andrew M. South, Tianxi Cai, Isaac S. Kohane
2020 A* conf
Learning to solve TV regularised problems with unrolled algorithms.
NeurIPS
Hamza Cherkaoui, Jeremias Sulam, Thomas Moreau
2020 A* conf
NeuMiss networks: differentiable programming for supervised learning with missing values.
NeurIPS
Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux
2020 J jnl
Neumann networks: differential programming for supervised learning with missing values.
CoRR
Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux
2020 A* conf
Super-efficiency of automatic differentiation for functions defined as a minimum.
ICML
Pierre Ablin, Gabriel Peyré, Thomas Moreau
2020 J jnl
Super-efficiency of automatic differentiation for functions defined as a minimum.
CoRR
Pierre Ablin, Gabriel Peyré, Thomas Moreau
2020 — conf
Wavelets in the Deep Learning Era.
EUSIPCO
Zaccharie Ramzi, Jean-Luc Starck, Thomas Moreau, Philippe Ciuciu
2019 J jnl
A Data Set for the Study of Human Locomotion with Inertial Measurements Units.
Image Process. Line
Charles Truong, Rémi Barrois-Müller, Thomas Moreau, Clément Provost, Aliénor Vienne-Jumeau, Albane Moreau, Pierre-Paul Vidal, Nicolas Vayatis, Stéphane Buffat, Alain P. Yelnik, Damien Ricard, Laurent Oudre
2019 J jnl
Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals.
CoRR
Thomas Moreau, Alexandre Gramfort
2019 A* conf
Learning step sizes for unfolded sparse coding.
NeurIPS
Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort
2019 J jnl
Learning step sizes for unfolded sparse coding.
CoRR
Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort
2019 Misc conf
Sparsity-based Blind Deconvolution of Neural Activation Signal in FMRI.
ICASSP
Hamza Cherkaoui, Thomas Moreau, Abderrahim Halimi, Philippe Ciuciu
2019 — conf
fMRI BOLD signal decomposition using a multivariate low-rank model.
EUSIPCO
Hamza Cherkaoui, Thomas Moreau, Abderrahim Halimi, Philippe Ciuciu
2018 A* conf
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding.
ICML
Thomas Moreau, Laurent Oudre, Nicolas Vayatis
2018 A* conf
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals.
NeurIPS
Tom Dupré la Tour, Thomas Moreau, Mainak Jas, Alexandre Gramfort
2018 J jnl
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals.
CoRR
Tom Dupré la Tour, Thomas Moreau, Mainak Jas, Alexandre Gramfort
2018 J jnl
Template-Based Step Detection with Inertial Measurement Units.
Sensors
Laurent Oudre, Rémi Barrois, Thomas Moreau, Charles Truong, Aliénor Vienne-Jumeau, Damien Ricard, Nicolas Vayatis, Pierre-Paul Vidal
2017 — —
Convolutional Sparse Representations - application to physiological signals and interpretability for Deep Learning. (Représentations Convolutives Parcimonieuses - application aux signaux physiologiques et interpétabilité de l'apprentissage profond).
Thomas Moreau
2017 J jnl
Distributed Convolutional Sparse Coding.
CoRR
Thomas Moreau, Laurent Oudre, Nicolas Vayatis
2017 — conf
Understanding Trainable Sparse Coding with Matrix Factorization.
ICLR (Poster)
Thomas Moreau, Joan Bruna
2016 J jnl
Post Training in Deep Learning with Last Kernel.
CoRR
Thomas Moreau, Julien Audiffren