Thomas Moreau

Orcid: 0000-0002-1523-3419

Affiliations:
  • Université Paris-Saclay, Inria, CEA, Palaiseau, France


According to our database1, Thomas Moreau authored at least 45 papers between 2016 and 2024.

Collaborative distances:
  • Dijkstra number2 of four.
  • Erdős number3 of four.

Timeline

Legend:

Book 
In proceedings 
Article 
PhD thesis 
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Links

Online presence:

On csauthors.net:

Bibliography

2024
S-JEPA: towards seamless cross-dataset transfer through dynamic spatial attention.
CoRR, 2024

2023
Wavelets in the Deep Learning Era.
J. Math. Imaging Vis., January, 2023

Using convolutional dictionary learning to detect task-related neuromagnetic transients and ageing trends in a large open-access dataset.
NeuroImage, 2023

Equivariant plug-and-play image reconstruction.
CoRR, 2023

Meta-Prior: Meta learning for Adaptive Inverse Problem Solvers.
CoRR, 2023

PAVI: Plate-Amortized Variational Inference.
CoRR, 2023

Test like you Train in Implicit Deep Learning.
CoRR, 2023

A Near-Optimal Algorithm for Bilevel Empirical Risk Minimization.
CoRR, 2023

FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels.
Proceedings of the International Conference on Machine Learning, 2023

Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals.
Proceedings of the International Conference on Machine Learning, 2023

2022
DiCoDiLe: Distributed Convolutional Dictionary Learning.
IEEE Trans. Pattern Anal. Mach. Intell., 2022

Data augmentation for learning predictive models on EEG: a systematic comparison.
CoRR, 2022

PAVI: Plate-Amortized Variational Inference.
CoRR, 2022

Deep invariant networks with differentiable augmentation layers.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

A framework for bilevel optimization that enables stochastic and global variance reduction algorithms.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

Benchopt: Reproducible, efficient and collaborative optimization benchmarks.
Proceedings of the Advances in Neural Information Processing Systems 35: Annual Conference on Neural Information Processing Systems 2022, 2022

CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals.
Proceedings of the Tenth International Conference on Learning Representations, 2022

SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models.
Proceedings of the Tenth International Conference on Learning Representations, 2022

Understanding approximate and unrolled dictionary learning for pattern recovery.
Proceedings of the Tenth International Conference on Learning Representations, 2022

DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals.
Proceedings of the Tenth International Conference on Learning Representations, 2022

2021
Multivariate semi-blind deconvolution of fMRI time series.
NeuroImage, 2021

DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals.
CoRR, 2021

CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals.
CoRR, 2021

Dictionary and prior learning with unrolled algorithms for unsupervised inverse problems.
CoRR, 2021

Leveraging Global Parameters for Flow-based Neural Posterior Estimation.
CoRR, 2021

HNPE: Leveraging Global Parameters for Neural Posterior Estimation.
Proceedings of the Advances in Neural Information Processing Systems 34: Annual Conference on Neural Information Processing Systems 2021, 2021

2020
International electronic health record-derived COVID-19 clinical course profiles: the 4CE consortium.
npj Digit. Medicine, 2020

Neumann networks: differential programming for supervised learning with missing values.
CoRR, 2020

NeuMiss networks: differentiable programming for supervised learning with missing values.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Learning to solve TV regularised problems with unrolled algorithms.
Proceedings of the Advances in Neural Information Processing Systems 33: Annual Conference on Neural Information Processing Systems 2020, 2020

Super-efficiency of automatic differentiation for functions defined as a minimum.
Proceedings of the 37th International Conference on Machine Learning, 2020

Wavelets in the Deep Learning Era.
Proceedings of the 28th European Signal Processing Conference, 2020

Extraction of Nystagmus Patterns from Eye-Tracker Data with Convolutional Sparse Coding.
Proceedings of the 42nd Annual International Conference of the IEEE Engineering in Medicine & Biology Society, 2020

2019
A Data Set for the Study of Human Locomotion with Inertial Measurements Units.
Image Process. Line, 2019

Distributed Convolutional Dictionary Learning (DiCoDiLe): Pattern Discovery in Large Images and Signals.
CoRR, 2019

Learning step sizes for unfolded sparse coding.
Proceedings of the Advances in Neural Information Processing Systems 32: Annual Conference on Neural Information Processing Systems 2019, 2019

Sparsity-based Blind Deconvolution of Neural Activation Signal in FMRI.
Proceedings of the IEEE International Conference on Acoustics, 2019

fMRI BOLD signal decomposition using a multivariate low-rank model.
Proceedings of the 27th European Signal Processing Conference, 2019

2018
Template-Based Step Detection with Inertial Measurement Units.
Sensors, 2018

Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals.
Proceedings of the Advances in Neural Information Processing Systems 31: Annual Conference on Neural Information Processing Systems 2018, 2018

DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding.
Proceedings of the 35th International Conference on Machine Learning, 2018

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).
PhD thesis, 2017

Distributed Convolutional Sparse Coding.
CoRR, 2017

Understanding Trainable Sparse Coding with Matrix Factorization.
Proceedings of the 5th International Conference on Learning Representations, 2017

2016
Post Training in Deep Learning with Last Kernel.
CoRR, 2016


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