59 citations · 145 across the 9 of their papers we have counts for
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cond-mat.stat-mech2024
Inferring the Isotropic-nematic Phase Transition with Generative Machine Learning
Eric R. Beyerle, Pratyush Tiwary
Contemporary work implies generative machine learning models are capable of learning the phase behavior in condensed matter systems such as the Ising model. In this Letter, we util…
cond-mat.stat-mech2023★ 26 cited
Recent advances in describing and driving crystal nucleation using machine learning and artificial intelligence
Eric R. Beyerle, Ziyue Zou, Pratyush Tiwary
With the advent of faster computer processors and especially graphics processing units (GPUs) over the last few decades, the use of data-intensive machine learning (ML) and artific…