Variational AI is redefining the unit economics of drug discovery through the power of generative AI. The founding machine learning (ML) team comes from leading AI research labs at Google, Microsoft, ...

Variational Autoencoders (VAE) on MNIST By stuyai, taught and made by Otzar Jaffe This project demonstrates the implementation of a Variational Autoencoder (VAE) using TensorFlow and Keras on the ...

SpaCAE (SPAtially Contrastive variational AutoEncoder) is a spatially contrastive variational autoencoder framework designed for spatial domains identification and highly sparse SRT data denoising.

This paper is a valuable step in multi-subject behavioral modeling using an extension of the Variational Autoencoder (VAE) framework. Using a novel partition of the latent space and in tandem with a ...

To summarize, the above results suggest that a variational autoencoder with 4 hidden layers in both of the encoder and decoder modules exhibited the best performance in terms of learning a meaningful ...

0000-0002-6043-9328 Department of Neurobiology, Duke University, Durham, United States Contribution Conceptualization, Writing – review and editing, Investigation, Funding acquisition, Project ...