Search Results - "Zhouyin, Zhanghao" :: K.UTB vyhledávací portál

Deep learning tight-binding approach for large-scale electronic simulations at finite temperatures with ab initio accuracy

by Gu, Qiangqiang, Zhouyin, Zhanghao, Pandey, Shishir Kumar, Zhang, Peng, Zhang, Linfeng, E, Weinan
Published in Nature communications (08.08.2024)

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Understanding Neural Networks with Logarithm Determinant Entropy Estimator

by Zhouyin, Zhanghao, Liu, Ding
Year of Publication 08.05.2021

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Learning local equivariant representations for quantum operators

by Zhouyin, Zhanghao, Gan, Zixi, Pandey, Shishir Kumar, Zhang, Linfeng, Gu, Qiangqiang
Year of Publication 08.07.2024

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Understanding Neural Networks with Logarithm Determinant Entropy Estimator

by Zhouyin, Zhanghao, Liu, Ding
Published in arXiv.org (08.05.2021)

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DeePTB: A deep learning-based tight-binding approach with $ab$ $initio$ accuracy

by Gu, Qiangqiang, Zhouyin, Zhanghao, Pandey, Shishir Kumar, Zhang, Peng, Zhang, Linfeng, E, Weinan
Year of Publication 10.07.2023

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Learning local equivariant representations for quantum operators

by Zhouyin, Zhanghao, Gan, Zixi, Pandey, Shishir Kumar, Zhang, Linfeng, Gu, Qiangqiang
Published in arXiv.org (16.07.2024)

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$DeePTB: A deep learning-based tight-binding approach with $ab$ $initio$ accuracy$

DeePTB: A deep learning-based tight-binding approach with $ab$ $initio$ accuracy

by Gu, Qiangqiang, Zhouyin, Zhanghao, Pandey, Shishir Kumar, Zhang, Peng, Zhang, Linfeng, Weinan, E
Published in arXiv.org (11.07.2023)

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Paper

Deep learning tight-binding approach for large-scale electronic simulations at finite temperatures with ab initio accuracy

Understanding Neural Networks with Logarithm Determinant Entropy Estimator

Learning local equivariant representations for quantum operators

Understanding Neural Networks with Logarithm Determinant Entropy Estimator

DeePTB: A deep learning-based tight-binding approach with $ab$ $initio$ accuracy

Learning local equivariant representations for quantum operators

DeePTB: A deep learning-based tight-binding approach with \(ab\) \(initio\) accuracy

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