← Authors

Thomas Moreau

20 papers · 2018–2025 · 5 conferences · across top CS/AI conferences

Achievements

🐝 Cross-Pollinator (12) 🗺️ Taxonomy Completionist (35) 🌉 Interdisciplinary Bridge 🐣 Hot Topic Early Bird 🌍 Conference Polyglot (5) 🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🌈 Renaissance Researcher (8) 👥 Mega-Team (21) 🔥 Unstoppable (8) 💎 Century Club (20) ⚡ Prolific Year (7) 🗃️ Keyword Collector (84)

Conferences

NIPS (8) ICLR (4) ICML (4) AISTATS (2) CVPR (2)

Top co-authors

Alexandre Gramfort (8) Pierre Ablin (5) Mathieu Dagréou (3) Samuel Vaiter (3) Cédric ROMMEL (2) Mathurin Massias (2) Tom Dupré la Tour (2) Guillaume Staerman (2) Cédric Allain (2) Benoît Malézieux (2)

Keywords

bilevel optimization (2) inverse problem (2) neural network (2) convolutional sparse coding (2) sparse representation (2) sparse coding (1) brain signal processing (1) network architecture (1) data augmentation (1) empirical risk minimization (1) supervised learning (1) sample complexity (1) image reconstruction (1) distributed computing (1) image restoration (1) signal processing (1) brain-computer interface (1) logistic regression (1) gradient estimation (1) automatic differentiation (1)

Papers

FiRe: Fixed-points of Restoration Priors for Solving Inverse Problems CVPR 2025
UNHaP: Unmixing Noise from Hawkes Processes AISTATS 2025
A Lower Bound and a Near-Optimal Algorithm for Bilevel Empirical Risk Minimization AISTATS 2024
Equivariant Plug-and-Play Image Reconstruction CVPR 2024
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels ICML 2023
Sliced-Wasserstein on Symmetric Positive Definite Matrices for M/EEG Signals ICML 2023
Benchopt: Reproducible, efficient and collaborative optimization benchmarks NIPS 2022
Deep invariant networks with differentiable augmentation layers NIPS 2022
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals ICLR 2022
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals ICLR 2022
Understanding approximate and unrolled dictionary learning for pattern recovery ICLR 2022
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models ICLR 2022
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms NIPS 2022
HNPE: Leveraging Global Parameters for Neural Posterior Estimation NIPS 2021
Super-efficiency of automatic differentiation for functions defined as a minimum ICML 2020
Learning to solve TV regularised problems with unrolled algorithms NIPS 2020
NeuMiss networks: differentiable programming for supervised learning with missing values. NIPS 2020
Learning step sizes for unfolded sparse coding NIPS 2019
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals NIPS 2018
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding ICML 2018