AI is being used to model gene regulation and predict cellular behavior from transcriptomic data. Learn how these tools aid ...

A Convolutional Variational Autoencoder (CVAE) was developed for this purpose. We demonstrate the efficacy of our approach using the transient data generated from the simulations. The simulation data ...

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 ...

for example, in the case of subjects roaming in an open-field. Overview of the Constrained Subspace Variational Autoencoder (CS-VAE). The latent space is divided in three parts: (1) the supervised ...

2018 - link The work describes a variational autoencoder that can add metal binding sites to protein sequences, or generate protein sequences for a given protein topology. These instructions will get ...

Abstract: To deal with the typically insufficiently labeled samples involved in practical spectroscopy measurements, a conditional variational autoencoder (CVAE ... A numerical simulation example and ...