← Authors

Alexandre Gramfort

43 papers · 2010–2024 · 8 conferences · across top CS/AI conferences

Achievements

🐣 Hot Topic Early Bird 🌈 Renaissance Researcher (5) πŸŒ‰ Interdisciplinary Bridge πŸ—ΊοΈ Taxonomy Completionist (10) 🧭 Keyword Pioneer 🌍 Conference Polyglot (8) πŸƒ Academic Marathon (14) 🐝 Cross-Pollinator (12) πŸ† Keyword Champion πŸ‘₯ Mega-Team (22) 🀝 Dynamic Duo (14) 🧬 Topic Evolution πŸ”¬ Deep Specialist (17) πŸ’Ž Century Club (43) πŸ—ƒοΈ Keyword Collector (188) πŸ”₯ Unstoppable (10) ⚑ Prolific Year (5) πŸ“ˆ Trend Setter

Conferences

NIPS (19) JMLR (7) AISTATS (6) ICML (6) ICLR (2) AUTOML (1) EMNLP (1) UAI (1)

Top co-authors

Joseph Salmon (14) Mathurin Massias (8) Thomas Moreau (8) Pierre Ablin (7) Bertrand Thirion (5) Olivier Fercoq (5) Quentin Bertrand (4) Hicham Janati (4) Samuel Vaiter (4) Charlotte Caucheteux (3)

Keywords

coordinate descent (6) optimal transport (5) screening rule (5) sparse regression (4) sparse optimization (3) hyperparameter optimization (3) sinkhorn algorithm (3) neural network (3) brain signal (3) duality gap (3) independent component analysis (3) convex optimization (3) multi-task learning (3) fmri analysis (2) domain adaptation (2) implicit differentiation (2) representation learning (2) brain activity (2) self-supervised learning (2) lasso regression (2)

Papers

emg2qwerty: A Large Dataset with Baselines for Touch Typing using Surface Electromyography NIPS 2024
Geodesic Optimization for Predictive Shift Adaptation on EEG data NIPS 2024
FaDIn: Fast Discretized Inference for Hawkes Processes with General Parametric Kernels ICML 2023
Convolution Monge Mapping Normalization for learning on sleep data NIPS 2023
L-C2ST: Local Diagnostics for Posterior Approximations in Simulation-Based Inference NIPS 2023
Implicit Differentiation for Fast Hyperparameter Selection in Non-Smooth Convex Learning JMLR 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
The optimal noise in noise-contrastive learning is not what you think UAI 2022
LassoBench: A High-Dimensional Hyperparameter Optimization Benchmark Suite for Lasso AUTOML 2022
Benchopt: Reproducible, efficient and collaborative optimization benchmarks NIPS 2022
Toward a realistic model of speech processing in the brain with self-supervised learning NIPS 2022
Deep invariant networks with differentiable augmentation layers NIPS 2022
mvlearn: Multiview Machine Learning in Python JMLR 2021
Model-based analysis of brain activity reveals the hierarchy of language in 305 subjects EMNLP 2021
Disentangling syntax and semantics in the brain with deep networks ICML 2021
HNPE: Leveraging Global Parameters for Neural Posterior Estimation NIPS 2021
Shared Independent Component Analysis for Multi-Subject Neuroimaging NIPS 2021
POT: Python Optimal Transport JMLR 2021
Debiased Sinkhorn barycenters ICML 2020
Statistical control for spatio-temporal MEG/EEG source imaging with desparsified mutli-task Lasso NIPS 2020
Modeling Shared responses in Neuroimaging Studies through MultiView ICA NIPS 2020
Spatio-temporal alignments: Optimal transport through space and time AISTATS 2020
Support recovery and sup-norm convergence rates for sparse pivotal estimation AISTATS 2020
Implicit differentiation of Lasso-type models for hyperparameter optimization ICML 2020
Dual Extrapolation for Sparse GLMs JMLR 2020
Handling correlated and repeated measurements with the smoothed multivariate square-root Lasso NIPS 2019
Learning step sizes for unfolded sparse coding NIPS 2019
Manifold-regression to predict from MEG/EEG brain signals without source modeling NIPS 2019
Wasserstein regularization for sparse multi-task regression AISTATS 2019
Stochastic algorithms with descent guarantees for ICA AISTATS 2019
Generalized Concomitant Multi-Task Lasso for Sparse Multimodal Regression AISTATS 2018
Celer: a Fast Solver for the Lasso with Dual Extrapolation ICML 2018
Multivariate Convolutional Sparse Coding for Electromagnetic Brain Signals NIPS 2018
Learning the Morphology of Brain Signals Using Alpha-Stable Convolutional Sparse Coding NIPS 2017
Anomaly Detection in Extreme Regions via Empirical MV-sets on the Sphere AISTATS 2017
On the Consistency of Ordinal Regression Methods JMLR 2017
Gap Safe Screening Rules for Sparsity Enforcing Penalties JMLR 2017
GAP Safe Screening Rules for Sparse-Group Lasso NIPS 2016
GAP Safe screening rules for sparse multi-task and multi-class models NIPS 2015
Mind the duality gap: safer rules for the Lasso ICML 2015
Scikit-learn: Machine Learning in Python JMLR 2011
Brain covariance selection: better individual functional connectivity models using population prior NIPS 2010