Unsupervised domain adaptation has provoked vast amount of attention and research in past decades. Among all the deep-based methods, the autoencoder-based approach have achieved sound performance for ...

Researchers at New York University have developed a new architecture for diffusion models that improves the semantic representation of the images they generate. “Diffusion Transformer with ...

Disentangled variational autoencoder (D-VAE) separates materials properties from the latent space by conditioning to make inverse materials design more efficient and transparent. It combines labeled ...

Dr. James McCaffrey of Microsoft Research tackles the process of examining a set of source data to find data items that are different in some way from the majority of the source items. Data anomaly ...