1.9k citations · 2k across the 4 of their papers we have counts for
4 papers
CADDA: Class-wise Automatic Differentiable Data Augmentation for EEG Signals
Cédric Rommel, Thomas Moreau, Joseph Paillard +1
Data augmentation is a key element of deep learning pipelines, as it informs the network during training about transformations of the input data that keep the label unchanged. Manu…
mvlearn: Multiview Machine Learning in Python
Ronan Perry, Gavin Mischler, Richard Guo +9
As data are generated more and more from multiple disparate sources, multiview data sets, where each sample has features in distinct views, have ballooned in recent years. However,…
API design for machine learning software: experiences from the scikit-learn project
Lars Buitinck, Gilles Louppe, Mathieu Blondel +12
Scikit-learn is an increasingly popular machine learning li- brary. Written in Python, it is designed to be simple and efficient, accessible to non-experts, and reusable in various…
Small-sample Brain Mapping: Sparse Recovery on Spatially Correlated Designs with Randomization and Clustering
Gael Varoquaux, Alexandre Gramfort, Bertrand Thirion
Functional neuroimaging can measure the brain?s response to an external stimulus. It is used to perform brain mapping: identifying from these observations the brain regions involve…