Alexandre Gramfort

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