Thomas Moreau
20 papers · 2018–2025 · 5 conferences · across top CS/AI conferences
Achievements
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🏃 Academic Marathon (7) 🧭 Keyword Pioneer 🌉 Interdisciplinary Bridge 🌍 Conference Polyglot (5) 🐝 Cross-Pollinator (12)
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Academic Marathon
(7)
🧭
Keyword Pioneer
🌈
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(8)
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(21)
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(8)
💎
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(20)
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(7)
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Keyword Collector
(84)
Conferences
NIPS (8)
ICLR (4)
ICML (4)
AISTATS (2)
CVPR (2)
Top co-authors
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