Rongzhi Dong

According to our database, Rongzhi Dong authored at least 13 papers between 2019 and 2024.

Collaborative distances:

• Dijkstra number of five.
• Erdős number of five.

2024

AlphaCrystal-II: Distance matrix based crystal structure prediction using deep learning.

Yuqi Song, Rongzhi Dong, Lai Wei, Qin Li, Jianjun Hu

CoRR, 2024

Structure-based out-of-distribution (OOD) materials property prediction: a benchmark study.

Sadman Sadeed Omee, Nihang Fu, Rongzhi Dong, Ming Hu, Jianjun Hu

CoRR, 2024

2023

Discovery of 2D Materials using Transformer Network-Based Generative Design.

Rongzhi Dong, Yuqi Song, Edirisuriya M. Dilanga Siriwardane, Jianjun Hu

Adv. Intell. Syst., December, 2023

Global Mapping of Structures and Properties of Crystal Materials.

Qinyang Li, Rongzhi Dong, Nihang Fu, Sadman Sadeed Omee, Lai Wei, Jianjun Hu

J. Chem. Inf. Model., June, 2023

Material transformers: deep learning language models for generative materials design.

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

Mach. Learn. Sci. Technol., March, 2023

Generative Design of inorganic compounds using deep diffusion language models.

Rongzhi Dong, Nihang Fu, Dirisuriya M. D. Siriwardane, Jianjun Hu

CoRR, 2023

2022

Scalable deeper graph neural networks for high-performance materials property prediction.

Sadman Sadeed Omee, Steph-Yves M. Louis, Nihang Fu, Lai Wei, Sourin Dey, Rongzhi Dong, Qinyang Li, Jianjun Hu

Patterns, 2022

Materials Property Prediction with Uncertainty Quantification: A Benchmark Study.

Daniel Varivoda, Rongzhi Dong, Sadman Sadeed Omee, Jianjun Hu

CoRR, 2022

Materials Transformers Language Models for Generative Materials Design: a benchmark study.

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

CoRR, 2022

2021

Crystal structure prediction of materials with high symmetry using differential evolution.

Wenhui Yang, Edirisuriya M. Dilanga Siriwardane, Rongzhi Dong, Yuxin Li, Jianjun Hu

CoRR, 2021

2020

Critical Temperature Prediction of Superconductors Based on Atomic Vectors and Deep Learning.

Shaobo Li, Yabo Dan, Xiang Li, Tiantian Hu, Rongzhi Dong, Zhuo Cao, Jianjun Hu

Symmetry, 2020

Computational Prediction of Critical Temperatures of Superconductors Based on Convolutional Gradient Boosting Decision Trees.

Yabo Dan, Rongzhi Dong, Zhuo Cao, Xiang Li, Chengcheng Niu, Shaobo Li, Jianjun Hu

IEEE Access, 2020

2019

Limited Data Rolling Bearing Fault Diagnosis With Few-Shot Learning.

Ansi Zhang, Shaobo Li, Yuxin Cui, Wanli Yang, Rongzhi Dong, Jianjun Hu

IEEE Access, 2019