Re - Implementation as well as few qualitatitive experiments for the state-of-the-art variational autoencoder technique of "Disentangling Factors of Variation with Cycle-Consistent Variational ...

Currently two models are supported, a simple Variational Autoencoder and a Disentangled version (beta-VAE). The model implementations can be found in the src/models directory. These models were ...

In recent years, autoencoders and their variants have emerged as effective tools for hyperspectral anomaly detection. Nevertheless, owing to the complex distribution of anomalous regions and the ...

We present the Multi-Level Variational Autoencoder (ML-VAE), a new deep probabilistic model for learning a disentangled representation of grouped data. The ML-VAE separates the latent representation ...