Ziang Wang

E2Former-V2: On-the-Fly Equivariant Attention with Linear Activation Memory

Equivariant Graph Neural Networks (EGNNs) have become a widely used approach for modeling 3D atomistic systems. However, mainstream architectures face critical scalability bottlenecks due to the explicit construction of geometric features or dense tensor products on \textit{every} edge. To overcome …