Representations from pretrained machine-learning interatomic potentials as coarse coordinates for material generation and evaluation
Read the original at arxiv.org→arXiv:2607.28776v1 Announce Type: new Abstract: Generative machine learning is increasingly used for inorganic crystal structure generation. Most models and the corresponding evaluation approaches rely on simple...
Original headline: "Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation"
Coverage timeline
- Aug 3, 04:00 UTC arXiv cs.LG lead source Representations from Pretrained Machine-Learning Interatomic Potentials as Coarse Coordinates for Material Generation and Evaluation