2 papers
cs.LG2026
Open Materials Generation with Inference-Time Reinforcement Learning
Philipp Hoellmer, Stefano Martiniani
Continuous-time generative models for crystalline materials enable inverse materials design by learning to predict stable crystal structures, but incorporating explicit target prop…
cs.LG2026
MolCryst-MLIPs: A Machine-Learned Interatomic Potentials Database for Molecular Crystals
Adam Lahouari, Shen Ai, Jihye Han +16
We present an open Molecular Crystal (MC) database of Machine-Learned Interatomic Potentials (MLIP) called MolCryst-MLIPs. The first release comprises fine-tuned MACE models for ni…