Si-Yu Hu

Architecture-agnostic knowledge distillation for machine-learning interatomic potentials.

Atomistic foundation models can achieve near-ab-initio accuracy and strong transferability across molecular and materials systems, but their large parameter counts lead to high inference latency and memory cost, limiting long-time-scale molecular dynamics and resource-constrained deployment. In many practical studies,...