Jie Chen

According to our database, Jie Chen authored at least 10 papers between 2021 and 2025.

Collaborative distances:

• Dijkstra number of four.
• Erdős number of four.

2025

Graph representation of local environments for learning high-entropy alloy properties.

Hengrui Zhang, Ruishu Huang, Jie Chen, James M. Rondinelli, Wei Chen

Mach. Learn. Sci. Technol., 2025

A Digital Twin Framework Utilizing Machine Learning for Robust Predictive Maintenance: Enhancing Tire Health Monitoring.

Vispi Karkaria, Jie Chen, Christopher Luey, Chase Siuta, Damien Lim, Robert Radulescu, Wei Chen

J. Comput. Inf. Sci. Eng., 2025

Uncertainty quantification driven machine learning for improving model accuracy in imbalanced regression tasks.

Tuba Dolar, Jie Chen, Wei Chen

Expert Syst. Appl., 2025

2024

Do Graph Neural Networks Work for High Entropy Alloys?

Hengrui Zhang, Ruishu Huang, Jie Chen, James M. Rondinelli, Wei Chen

CoRR, 2024

Adaptive Catalyst Discovery Using Multicriteria Bayesian Optimization with Representation Learning.

Jie Chen, Pengfei Ou, Yuxin Chang, Hengrui Zhang, Xiao-Yan Li, Edward H. Sargent, Wei Chen

CoRR, 2024

Towards a Digital Twin Framework in Additive Manufacturing: Machine Learning and Bayesian Optimization for Time Series Process Optimization.

Vispi Karkaria, Anthony Goeckner, Rujing Zha, Jie Chen, Jianjing Zhang, Qi Zhu, Jian Cao, Robert X. Gao, Wei Chen

CoRR, 2024

2023

MolSets: Molecular Graph Deep Sets Learning for Mixture Property Modeling.

Hengrui Zhang, Jie Chen, James M. Rondinelli, Wei Chen

CoRR, 2023

2022

Physics-guided mixture density networks for uncertainty quantification.

Jie Chen, Yang Yu, Yongming Liu

Reliab. Eng. Syst. Saf., 2022

Neural Optimization Machine: A Neural Network Approach for Optimization.

Jie Chen, Yongming Liu

CoRR, 2022

2021

Probabilistic physics-guided machine learning for fatigue data analysis.

Jie Chen, Yongming Liu

Expert Syst. Appl., 2021