Generating synthetic data is useful when you have imbalanced training data for a particular class, for example, generating synthetic females in a dataset of employees that has many males but few ...

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 ...

CatDRX is a generative AI framework developed at Institute of Science Tokyo, which enables the design of new chemical catalysts based on the specific chemical reactions in which they are used. The ...

Researchers develop an AI-based platform that integrates reaction data with catalyst performance for the design of new ...

The research team included, back row, from left, Shih-I (Harry) Tan, Nilmani Singh, Aashutosh Boob, and front row, from left, Teresa Martin, Li-Qing Chen, and Huimin Zhao. The mitochondrion, often ...

Dr. James McCaffrey of Microsoft Research provides full code and step-by-step examples of anomaly detection, used to find items in a dataset that are different from the majority for tasks like ...

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 ...