In recent years, clustering methods based on deep generative models have received great attention in various unsupervised applications, due to their capabilities for learning promising latent ...

Variational Autoencoder in tensorflow and pytorch Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more ...

About This GitHub repository hosts implementations of Variational Autoencoder (VAE) and Denoising Convolutional VAE specifically designed for exploring protein-ligand interactions.

Accurate detection of anomalies in multivariate time series data has attracted much attention due to its importance in a wide range of applications. Since it is difficult to obtain accurately labeled ...

A well-trained variational autoencoder is capable of projecting trajectories onto a low-dimensional latent space, which can be used to produce realistic conformations, either similar or distant to the ...