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cond-mat.mtrl-sci2024★ 14 cited
CrystalFlow: A Flow-Based Generative Model for Crystalline Materials
Xiaoshan Luo, Zhenyu Wang, Qingchang Wang +4
Deep learning-based generative models have emerged as powerful tools for modeling complex data distributions and generating high-fidelity samples, offering a transformative approac…
cond-mat.mtrl-sci2024★ 72 cited
Deep learning generative model for crystal structure prediction
Xiaoshan Luo, Zhenyu Wang, Pengyue Gao +4
Recent advances in deep learning generative models (GMs) have created high capabilities in accessing and assessing complex high-dimensional data, allowing superior efficiency in na…