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Rongzhi Dong
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2020 – today
- 2024
- [i8]Sadman Sadeed Omee, Nihang Fu, Rongzhi Dong, Ming Hu, Jianjun Hu:
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study. CoRR abs/2401.08032 (2024) - [i7]Yuqi Song, Rongzhi Dong, Lai Wei, Qin Li, Jianjun Hu:
AlphaCrystal-II: Distance matrix based crystal structure prediction using deep learning. CoRR abs/2404.04810 (2024) - 2023
- [j7]Rongzhi Dong
, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
Discovery of 2D Materials using Transformer Network-Based Generative Design. Adv. Intell. Syst. 5(12) (2023) - [j6]Qinyang Li, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee
Global Mapping of Structures and Properties of Crystal Materials. J. Chem. Inf. Model. 63(12): 3814-3826 (2023) - [j5]Nihang Fu, Lai Wei
Material transformers: deep learning language models for generative materials design. Mach. Learn. Sci. Technol. 4(1): 15001 (2023) - [i6]Rongzhi Dong, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu:
Discovery of 2D materials using Transformer Network based Generative Design. CoRR abs/2301.05824 (2023) - [i5]Rongzhi Dong, Nihang Fu, Dirisuriya M. D. Siriwardane, Jianjun Hu:
Generative Design of inorganic compounds using deep diffusion language models. CoRR abs/2310.00475 (2023) - 2022
- [j4]Sadman Sadeed Omee
Scalable deeper graph neural networks for high-performance materials property prediction. Patterns 3(5): 100491 (2022) - [i4]Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu:
Materials Transformers Language Models for Generative Materials Design: a benchmark study. CoRR abs/2206.13578 (2022) - [i3]Daniel Varivoda, Rongzhi Dong, Sadman Sadeed Omee, Jianjun Hu:
Materials Property Prediction with Uncertainty Quantification: A Benchmark Study. CoRR abs/2211.02235 (2022) - 2021
- [i2]Wenhui Yang, Edirisuriya M. Dilanga Siriwardane, Rongzhi Dong, Yuxin Li, Jianjun Hu:
Crystal structure prediction of materials with high symmetry using differential evolution. CoRR abs/2104.09764 (2021) - [i1]Sadman Sadeed Omee, Steph-Yves M. Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu:
Scalable deeper graph neural networks for high-performance materials property prediction. CoRR abs/2109.12283 (2021) - 2020
- [j3]Yabo Dan
Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees. IEEE Access 8: 57868-57878 (2020) - [j2]Shaobo Li
Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning. Symmetry 12(2): 262 (2020)
2010 – 2019
- 2019
- [j1]Ansi Zhang
Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning. IEEE Access 7: 110895-110904 (2019)
Coauthor Index
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