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Jianjun Hu
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Discovery of 2D materials using Transformer Network based Generative Design


Jan 14, 2023
Rongzhi Dong, Yuqi Song, Edirisuriya M. D. Siriwardane, Jianjun Hu

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* 16 pages 
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Composition based oxidation state prediction of materials using deep learning


Nov 29, 2022
Nihang Fu, Jeffrey Hu, Ying Feng, Gregory Morrison, Hans-Conrad zur Loye, Jianjun Hu

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* 16 pages 
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Materials Property Prediction with Uncertainty Quantification: A Benchmark Study


Nov 11, 2022
Daniel Varivoda, Rongzhi Dong, Sadman Sadeed Omee, Jianjun Hu

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Probabilistic Generative Transformer Language models for Generative Design of Molecules


Sep 20, 2022
Lai Wei, Nihang Fu, Yuqi Song, Qian Wang, Jianjun Hu

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* 13 pages 
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Materials Transformers Language Models for Generative Materials Design: a benchmark study


Jun 27, 2022
Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu

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* 18 pages 
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Crystal Transformer: Self-learning neural language model for Generative and Tinkering Design of Materials


Apr 25, 2022
Lai Wei, Qinyang Li, Yuqi Song, Stanislav Stefanov, Edirisuriya M. D. Siriwardane, Fanglin Chen, Jianjun Hu

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* 18 pages 
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Physics Guided Generative Adversarial Networks for Generations of Crystal Materials with Symmetry Constraints


Mar 27, 2022
Yong Zhao, Edirisuriya M. Dilanga Siriwardane, Zhenyao Wu, Ming Hu, Nihang Fu, Jianjun Hu

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Semi-supervised teacher-student deep neural network for materials discovery


Dec 12, 2021
Daniel Gleaves, Edirisuriya M. Dilanga Siriwardane, Yong Zhao, Nihang Fu, Jianjun Hu

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* 18 pages 
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Physics guided deep learning generative models for crystal materials discovery


Dec 07, 2021
Yong Zhao, Edirisuriya MD Siriwardane, Jianjun Hu

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