most citedEfficient prediction of potential energy surface and physical properties with Kolmogorov-Arnold Networks

1 citations · 1 across the 2 of their papers we have counts for

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2 papers

physics.comp-ph2024★ 1 cited

Efficient prediction of potential energy surface and physical properties with Kolmogorov-Arnold Networks

Rui Wang, Hongyu Yu, Yang Zhong +1

The application of machine learning methodologies for predicting properties within materials science has garnered significant attention. Among recent advancements, Kolmogorov-Arnol…

physics.comp-ph2023

Transferable Machine Learning Approach for Predicting Electronic Structures of Charged Defects

Yuxing Ma, Yang Zhong, Yu Hongyu +2

The study of the electronic properties of charged defects is crucial for our understanding of various electrical properties of materials. However, the high computational cost of de…