Reference implementation for a variational autoencoder in TensorFlow and PyTorch. I recommend the PyTorch version. It includes an example of a more expressive variational family, the inverse ...

Aiming at the problem of sparse data and user cold start in a single domain for collaborative filtering, this paper proposes a cross-domain recommendation model called cross-domain variational ...

The de novo design of drug molecules is recognized as a time-consuming and costly process, and computational approaches have been applied in each stage of the drug discovery pipeline. Variational ...

Schematic diagram of Dear-DIA. view more . ... Next, Dear-DIA uses a variational autoencoder to extract the peak features of fragment ions and maps the features into Euclidean space, ...

Training a Variational Autoencoder Training a VAE involves two measures of similarity (or equivalently measures of loss). First, you must measure how closely the reconstructed output matches the ...

In this paper, we proposed a neural network (variational autoencoder) architecture that is used to generate an ECG corresponding to a single cardiac cycle. Our method generates synthetic ECGs using ...