Machine Learning based parameter tuning strategy for MMC based topology optimization. - Xinchao Jiang; Hu Wang 002; Yu Li; Kangjia Mo (Adv. Eng. Softw., 2020)

A Physics-Data-Driven Bayesian Method for Heat Conduction Problems. - Xinchao Jiang; Hu Wang 002; Yu Li (CoRR, 2021)

An E-PINN assisted practical uncertainty quantification for inverse problems. - Xinchao Jiang; Xin Wang; Ziming Wen; Enying Li; Hu Wang 002 (CoRR, 2022)

A novel reduced basis method for adjoint sensitivity analysis of dynamic topology optimization. - Shuhao Li; Hu Wang 002; Jichao Yin; Xinchao Jiang; Yaya Zhang (CoRR, 2023)

Resolution-independent generative models based on operator learning for physics-constrained Bayesian inverse problems. - Xinchao Jiang; Xin Wang; Ziming Wen; Hu Wang 002 (CoRR, 2023)

A ranking prediction strategy assisted automatic model selection method. - Jinyang Li; Hu Wang 002; Hong Luo; Xinchao Jiang; Enying Li (Adv. Eng. Informatics, 2023)

Manifold learning-assisted uncertainty quantification of system parameters in the fiber metal laminates hot forming process. - Xin Wang; Xinchao Jiang; Hu Wang 002; Guangyao Li (J. Intell. Manuf., 2025)