Jianwei Shuai's team and Jiahuai Han's team at Xiamen University have developed a deep autoencoder-based data-independent acquisition data analysis software for protein mass spectrometry, which ...

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 ...

One of the more powerful – and visually stunning – advances in generative AI has been the development of Stable Diffusion models. These models are used for image generation, image denoising, ...