Variational Autoencoders (VAEs) are an artificial neural network architecture to generate new data. They are similar to regular autoencoders, which consist of an encoder and decoder. The encoder takes ...

Here we present biVI, which combines the variational autoencoder framework of scVI with biophysical models describing the transcription and splicing kinetics of RNA molecules. We demonstrate on ...