If you are already familiar with variational autoencoders or wish to find the implementation straight away, I'd suggest to skip this section. In any other case, it may be worth the read. ### How do ...

The unlabelled aspect of data doesn’t seem to be a hurdle any more. A group of researchers from Munich have introduced a new flavor of Variational Autoencoder (VAE) that interpolates between different ...

Variational autoencoder is one of the computer-aided design methods which explores the chemical space based on an existing molecular dataset. Quantum machine learning has emerged as an atypical ...

However, previous works which followed data-free constraint still suffer ... In order to alleviate catastrophic forgetting, we propose the residual variational autoencoder (RVAE) to enhance LAMOL, a ...

I would really recommend my blog "What is a Variational Autoencoder (VAE)?" if you are interested in understanding VAEs in more detail. However, based on the high-level recap above, I hope that you ...