Rongzhi Dong

Publication Activity (10 Years)

Years Active: 2019-2024
Publications (10 Years): 15

Top Topics

Distance Matrix

Adaptive Differential Evolution

Artificial Neural Networks To Predict

Top Venues

Mach. Learn. Sci. Technol.

Publications

Sadman Sadeed Omee, Nihang Fu, Rongzhi Dong, Ming Hu, Jianjun Hu
Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study. CoRR (2024)
Yuqi Song, Rongzhi Dong, Lai Wei, Qin Li, Jianjun Hu
AlphaCrystal-II: Distance matrix based crystal structure prediction using deep learning. CoRR (2024)
Rongzhi Dong, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
Discovery of 2D materials using Transformer Network based Generative Design. CoRR (2023)
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)
Qinyang Li, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee, Lai Wei, Jianjun Hu
Global Mapping of Structures and Properties of Crystal Materials. J. Chem. Inf. Model. 63 (12) (2023)
Nihang Fu, Lai Wei, Yuqi Song, Qinyang Li, Rui Xin, Sadman Sadeed Omee, Rongzhi Dong, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu
Material transformers: deep learning language models for generative materials design. Mach. Learn. Sci. Technol. 4 (1) (2023)
Rongzhi Dong, Nihang Fu, Dirisuriya M. D. Siriwardane, Jianjun Hu
Generative Design of inorganic compounds using deep diffusion language models. CoRR (2023)
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. Patterns 3 (5) (2022)
Daniel Varivoda, Rongzhi Dong, Sadman Sadeed Omee, Jianjun Hu
Materials Property Prediction with Uncertainty Quantification: A Benchmark Study. CoRR (2022)
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 (2022)
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 (2021)
Wenhui Yang, Edirisuriya M. Dilanga Siriwardane, Rongzhi Dong, Yuxin Li, Jianjun Hu
Crystal structure prediction of materials with high symmetry using differential evolution. CoRR (2021)
Yabo Dan, Rongzhi Dong, Zhuo Cao, Xiang Li, Chengcheng Niu, Shaobo Li, Jianjun Hu
Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees. IEEE Access 8 (2020)
Shaobo Li, Yabo Dan, Xiang Li, Tiantian Hu, Rongzhi Dong, Zhuo Cao, Jianjun Hu
Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning. Symmetry 12 (2) (2020)
Ansi Zhang, Shaobo Li, Yuxin Cui, Wanli Yang, Rongzhi Dong, Jianjun Hu
Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning. IEEE Access 7 (2019)