Tag
Introduces MEET, a memory-efficient E(3) equivariant transformer for full-atom peptide design, integrated with a VAE and latent diffusion pipeline to achieve linear memory scaling and improved generation quality.
This paper investigates the role of group-equivariant architectures in neural fluid dynamics surrogates, introducing the AB-GATr model. It finds that equivariance is beneficial when data lacks strong alignment, but can degrade performance on highly aligned datasets.