2 papers
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…
stat.ML2020
Geometry-Aware Hamiltonian Variational Auto-Encoder
Clément Chadebec, Clément Mantoux, Stéphanie Allassonnière
Variational auto-encoders (VAEs) have proven to be a well suited tool for performing dimensionality reduction by extracting latent variables lying in a potentially much smaller dim…