103 citations · 129 across the 11 of their papers we have counts for
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stat.ML2021★ 103 cited
Data Augmentation in High Dimensional Low Sample Size Setting Using a Geometry-Based Variational Autoencoder
Clément Chadebec, Elina Thibeau-Sutre, Ninon Burgos +1
In this paper, we propose a new method to perform data augmentation in a reliable way in the High Dimensional Low Sample Size (HDLSS) setting using a geometry-based variational aut…
stat.ML2021
Data Augmentation with Variational Autoencoders and Manifold Sampling
Clément Chadebec, Stéphanie Allassonnière
We propose a new efficient way to sample from a Variational Autoencoder in the challenging low sample size setting. This method reveals particularly well suited to perform data aug…