3 citations · 4 across the 2 of their papers we have counts for
2 papers
cond-mat.mtrl-sci2025★ 3 cited
CrystalGRW: Generative Modeling of Crystal Structures with Targeted Properties via Geodesic Random Walks
Krit Tangsongcharoen, Teerachote Pakornchote, Chayanon Atthapak +6
Determining whether a candidate crystalline material is thermodynamically stable depends on identifying its true ground-state structure, a central challenge in computational materi…
cs.LG2023★ 1 cited
Diffusion probabilistic models enhance variational autoencoder for crystal structure generative modeling
Teerachote Pakornchote, Natthaphon Choomphon-anomakhun, Sorrjit Arrerut +4
The crystal diffusion variational autoencoder (CDVAE) is a machine learning model that leverages score matching to generate realistic crystal structures that preserve crystal symme…