ISA-VAE: Independent Subspace Analysis with Variational Autoencoders

Recent work has shown increased interest in using the Variational Autoencoder (VAE) framework to discover interpretable representations of data in an unsupervised way. These methods have focussed largely on modifying the variational cost function to achieve this goal... (read more)

PDF Abstract
No code implementations yet. Submit your code now

Datasets


  Add Datasets introduced or used in this paper

Results from the Paper


  Submit results from this paper to get state-of-the-art GitHub badges and help the community compare results to other papers.

Methods used in the Paper


METHOD TYPE
ICA
Dimensionality Reduction
Beta-VAE
Generative Models
AutoEncoder
Generative Models
VAE
Generative Models