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Thomas Moreau
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2020 – today
- 2022
- [j8]Thomas Moreau
, Alexandre Gramfort
:
DiCoDiLe: Distributed Convolutional Dictionary Learning. IEEE Trans. Pattern Anal. Mach. Intell. 44(5): 2426-2437 (2022) - [j7]Adriana M. Santos-Ferreira
, José C. B. da Silva
, Jorge M. Magalhães
, Samira Amraoui, Thomas Moreau, Claire Maraldi, François Boy, Nicolas Picot, Franck Borde:
Effects of Surface Wave Breaking Caused by Internal Solitary Waves in SAR Altimeter: Sentinel-3 Copernicus Products and Advanced New Products. Remote. Sens. 14(3): 587 (2022) - [i16]Mathieu Dagréou, Pierre Ablin, Samuel Vaiter, Thomas Moreau:
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms. CoRR abs/2201.13409 (2022) - [i15]Cédric Rommel, Thomas Moreau, Alexandre Gramfort:
Deep invariant networks with differentiable augmentation layers. CoRR abs/2202.02142 (2022) - [i14]Louis Rouillard, Thomas Moreau, Demian Wassermann:
PAVI: Plate-Amortized Variational Inference. CoRR abs/2206.05111 (2022) - 2021
- [j6]Hamza Cherkaoui, Thomas Moreau, Abderrahim Halimi
, Claire Leroy, Philippe Ciuciu:
Multivariate semi-blind deconvolution of fMRI time series. NeuroImage 241: 118418 (2021) - [c15]Pedro Rodrigues, Thomas Moreau, Gilles Louppe, Alexandre Gramfort:
HNPE: Leveraging Global Parameters for Neural Posterior Estimation. NeurIPS 2021: 13432-13443 - [i13]Pedro L. C. Rodrigues, Thomas Moreau, Gilles Louppe
, Alexandre Gramfort:
Leveraging Global Parameters for Flow-based Neural Posterior Estimation. CoRR abs/2102.06477 (2021) - [i12]Zaccharie Ramzi, Florian Mannel, Shaojie Bai, Jean-Luc Starck, Philippe Ciuciu, Thomas Moreau
:
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models. CoRR abs/2106.00553 (2021) - [i11]Benoît Malézieux, Thomas Moreau, Matthieu Kowalski:
Dictionary and prior learning with unrolled algorithms for unsupervised inverse problems. CoRR abs/2106.06338 (2021) - [i10]Cédric Rommel, Thomas Moreau, Alexandre Gramfort:
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals. CoRR abs/2106.13695 (2021) - [i9]Cédric Allain, Alexandre Gramfort, Thomas Moreau, A. Preprint:
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals. CoRR abs/2112.06652 (2021) - 2020
- [j5]Sébastien Clerc
, Craig Donlon, Franck Borde, Nicolas Lamquin, Samuel E. Hunt
, Dave Smith
, Malcolm McMillan
, Jonathan P. D. Mittaz, Emma Woolliams
, Matthew L. Hammond
, Christopher J. Banks
, Thomas Moreau, Bruno Picard
, Matthias Raynal, Pierre Rieu, Adrien Guérou:
Benefits and Lessons Learned from the Sentinel-3 Tandem Phase. Remote. Sens. 12(17): 2668 (2020) - [c14]Clément Lalanne, Maxence Rateaux, Laurent Oudre, Matthieu P. Robert, Thomas Moreau:
Extraction of Nystagmus Patterns from Eye-Tracker Data with Convolutional Sparse Coding. EMBC 2020: 928-931 - [c13]Zaccharie Ramzi, Jean-Luc Starck, Thomas Moreau, Philippe Ciuciu:
Wavelets in the Deep Learning Era. EUSIPCO 2020: 1417-1421 - [c12]Pierre Ablin, Gabriel Peyré, Thomas Moreau:
Super-efficiency of automatic differentiation for functions defined as a minimum. ICML 2020: 32-41 - [c11]José C. B. da Silva, Adriana M. Santos-Ferreira, Pierre Rieu, Thomas Moreau, Franck Borde, Francois Boy, Claire Maraldi, Nicolas Picot, Craig Donlon:
Detection of Internal Solitary Waves with Conventional and Advanced SAR Altimetry Processing Methods: Preliminary Results. IGARSS 2020: 3521-3524 - [c10]Hamza Cherkaoui, Jeremias Sulam, Thomas Moreau:
Learning to solve TV regularised problems with unrolled algorithms. NeurIPS 2020 - [c9]Marine Le Morvan, Julie Josse, Thomas Moreau, Erwan Scornet, Gaël Varoquaux:
NeuMiss networks: differentiable programming for supervised learning with missing values. NeurIPS 2020 - [i8]Pierre Ablin, Gabriel Peyré, Thomas Moreau
:
Super-efficiency of automatic differentiation for functions defined as a minimum. CoRR abs/2002.03722 (2020) - [i7]Marine Le Morvan, Julie Josse, Thomas Moreau
, Erwan Scornet, Gaël Varoquaux:
Neumann networks: differential programming for supervised learning with missing values. CoRR abs/2007.01627 (2020) - [i6]Clément Lalanne, Maxence Rateaux, Laurent Oudre, Matthieu P. Robert, Thomas Moreau
:
Extraction of Nystagmus Patterns from Eye-Tracker Data with Convolutional Sparse Coding. CoRR abs/2011.14962 (2020)
2010 – 2019
- 2019
- [j4]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:
A Data Set for the Study of Human Locomotion with Inertial Measurements Units. Image Process. Line 9: 381-390 (2019) - [c8]Hamza Cherkaoui, Thomas Moreau, Abderrahim Halimi
, Philippe Ciuciu:
fMRI BOLD signal decomposition using a multivariate low-rank model. EUSIPCO 2019: 1-5 - [c7]Hamza Cherkaoui, Thomas Moreau
, Abderrahim Halimi
, Philippe Ciuciu:
Sparsity-based Blind Deconvolution of Neural Activation Signal in FMRI. ICASSP 2019: 1323-1327 - [c6]Pierre Ablin, Thomas Moreau, Mathurin Massias, Alexandre Gramfort:
Learning step sizes for unfolded sparse coding. NeurIPS 2019: 13100-13110 - [i5]Thomas Moreau
, Alexandre Gramfort:
Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals. CoRR abs/1901.09235 (2019) - [i4]Pierre Ablin, Thomas Moreau
, Mathurin Massias, Alexandre Gramfort:
Learning step sizes for unfolded sparse coding. CoRR abs/1905.11071 (2019) - 2018
- [j3]Laurent Oudre
, Rémi Barrois, Thomas Moreau
, Charles Truong
, Aliénor Vienne-Jumeau, Damien Ricard, Nicolas Vayatis, Pierre-Paul Vidal
:
Template-Based Step Detection with Inertial Measurement Units. Sensors 18(11): 4033 (2018) - [c5]Thomas Moreau, Laurent Oudre
, Nicolas Vayatis:
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding. ICML 2018: 3623-3631 - [c4]Tom Dupré la Tour, Thomas Moreau, Mainak Jas, Alexandre Gramfort:
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals. NeurIPS 2018: 3296-3306 - [i3]Tom Dupré la Tour, Thomas Moreau
, Mainak Jas, Alexandre Gramfort:
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals. CoRR abs/1805.09654 (2018) - 2017
- [b1]Thomas Moreau:
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). University of Paris-Saclay, France, 2017 - [j2]Francois Boy
, Jean-Damien Desjonqueres, Nicolas Picot, Thomas Moreau, Matthias Raynal:
CryoSat-2 SAR-Mode Over Oceans: Processing Methods, Global Assessment, and Benefits. IEEE Trans. Geosci. Remote. Sens. 55(1): 148-158 (2017) - [c3]Thomas Moreau, Joan Bruna:
Understanding Trainable Sparse Coding with Matrix Factorization. ICLR (Poster) 2017 - [i2]Thomas Moreau, Laurent Oudre, Nicolas Vayatis:
Distributed Convolutional Sparse Coding. CoRR abs/1705.10087 (2017) - 2016
- [i1]Thomas Moreau
, Julien Audiffren:
Post Training in Deep Learning with Last Kernel. CoRR abs/1611.04499 (2016) - 2015
- [j1]Abderrahim Halimi
, Corinne Mailhes, Jean-Yves Tourneret, Francois Boy, Thomas Moreau:
Including Antenna Mispointing in a Semi-Analytical Model for Delay/Doppler Altimetry. IEEE Trans. Geosci. Remote. Sens. 53(2): 598-608 (2015) - 2014
- [c2]Abderrahim Halimi, Corinne Mailhes, Jean-Yves Tourneret, Thomas Moreau, Francois Boy:
Exploiting time and frequency information for Delay/Doppler altimetry. EUSIPCO 2014: 1088-1092 - [c1]Abderrahim Halimi
, Corinne Mailhes, Jean-Yves Tourneret, Francois Boy, Thomas Moreau:
A generalized semi-analytical model for delay/Doppler altimetry. IGARSS 2014: 5126-5129
Coauthor Index

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