Bryan R. Goldsmith

Equivariant-Free Transformer-Autoencoded Latent Flow Matching, a two-stage generative framework that relies entirely on a single fixed-dimensional molecule-level latent representation to generate variable-size molecules, is introduced.

Forget unreliable uncertainty estimates: this active learning method uses influence functions to directly optimize for your desired goal, slashing data needs in diverse tasks.