Thomas Moreau
20 papers · 2018–2025 · 5 venues · across top CS/AI venues
Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.
Achievements
Jump to papers ↓+8 more ↓ Show less ↑
🗺️ Taxonomy Completionist (41) 🏃 Academic Marathon · Sprint 🌍 Conference Polyglot · Silver 🌉 Interdisciplinary Bridge · Gold 🐣 Hot Topic Early Bird
👥
Mega-Team · Squad
🔬
Deep Specialist
(10)
🌈
Renaissance Researcher
(6)
🔥
Unstoppable · Bronze
⚡
Prolific Year · Productive
💎
Century Club · Bronze
📈
Trend Setter
🗃️
Keyword Collector
(105)
Top co-authors
Research topics
Machine Learning
(18)
Optimization & Theory
(14)
Core Methods
(9)
Deep Learning
(7)
Mathematics & Optimization
(6)
Optimization
(6)
Healthcare & Medicine
(4)
Architectures
(4)
Research
(4)
Artificial Intelligence
(3)
Computer Vision
(3)
Application Areas
(3)
Learning Types
(3)
Data Science & Analytics
(2)
Bayesian & Probabilistic
(2)
Keywords
bilevel optimization
(4)
sparse representation
(3)
sparse coding
(2)
hawkes process
(2)
alternating minimization
(2)
empirical risk minimization
(2)
inverse problem
(2)
stochastic optimization
(2)
neural network
(2)
convolutional sparse coding
(2)
brain signal processing
(1)
data augmentation
(1)
supervised learning
(1)
sample complexity
(1)
hyperparameter optimization
(1)
image restoration
(1)
reproducible research
(1)
gradient estimation
(1)
logistic regression
(1)
domain adaptation
(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
A framework for bilevel optimization that enables stochastic and global variance reduction algorithms
NeurIPS 2022
Benchopt: Reproducible, efficient and collaborative optimization benchmarks
NeurIPS 2022
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals
ICLR 2022
Deep invariant networks with differentiable augmentation layers
NeurIPS 2022
DriPP: Driven Point Processes to Model Stimuli Induced Patterns in M/EEG Signals
ICLR 2022
SHINE: SHaring the INverse Estimate from the forward pass for bi-level optimization and implicit models
ICLR 2022
Understanding approximate and unrolled dictionary learning for pattern recovery
ICLR 2022
HNPE: Leveraging Global Parameters for Neural Posterior Estimation
NeurIPS 2021
Learning to solve TV regularised problems with unrolled algorithms
NeurIPS 2020
NeuMiss networks: differentiable programming for supervised learning with missing values.
NeurIPS 2020
Super-efficiency of automatic differentiation for functions defined as a minimum
ICML 2020
Learning step sizes for unfolded sparse coding
NeurIPS 2019
DICOD: Distributed Convolutional Coordinate Descent for Convolutional Sparse Coding
ICML 2018
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals
NeurIPS 2018