Alexandre Gramfort

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

Achievements

+13 more ↓

🧭 Keyword Pioneer 🌈 Renaissance Researcher (5) 🌉 Interdisciplinary Bridge 🗺️ Taxonomy Completionist (10) 🌍 Conference Polyglot (8)

🌍 Conference Polyglot (8) 🏃 Academic Marathon (14) 🐝 Cross-Pollinator (12) 🏆 Keyword Champion 👥 Mega-Team (22) 🤝 Dynamic Duo (14) 🧬 Topic Evolution 🔬 Deep Specialist (17) 💎 Century Club (43) 🗃️ Keyword Collector (188) 🔥 Unstoppable (10) ⚡ Prolific Year (5) 📈 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