Jisu Kim

An efficient forgetting-aware fine-tuning framework for pretrained universal machine-learning interatomic potentials

2025 · arXiv (Cornell University)

Pretrained universal machine-learning interatomic potentials (MLIPs) have revolutionized computational materials science by enabling rapid atomistic simulations as efficient alternatives to ab initio methods. Fine-tuning pretrained MLIPs offers a practical approach to improving accuracy for materials …