Jay L. Kaplan

NEMORA: Neural Equivariant Multipole Operators for Long-Range Atomistic Learning

Equivariant graph neural networks have emerged as foundational architectures for machine-learned interatomic potentials, approaching quantum-chemical accuracy at a fraction of the computational cost. These models describe local atomic environments accurately, but finite spatial cutoffs truncate long-range information f...