Xiaolong He

According to our database, Xiaolong He authored at least 13 papers between 2021 and 2025.

Collaborative distances:

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

2025

Thermodynamically Consistent Latent Dynamics Identification for Parametric Systems.

Xiaolong He, Yeonjong Shin, Anthony Gruber, Sohyeon Jung, Kookjin Lee, Youngsoo Choi

CoRR, June, 2025

2024

Physics-informed active learning with simultaneous weak-form latent space dynamics identification.

Xiaolong He, April Tran, David M. Bortz, Youngsoo Choi

CoRR, 2024

A Comprehensive Review of Latent Space Dynamics Identification Algorithms for Intrusive and Non-Intrusive Reduced-Order-Modeling.

Christophe Bonneville, Xiaolong He, April Tran, Jun Sur Richard Park, William Fries, Daniel A. Messenger, Siu Wun Cheung, Yeonjong Shin, David M. Bortz, Debojyoti Ghosh, Jiun-Shyan Chen, Jonathan L. Belof, Youngsoo Choi

CoRR, 2024

2023

gLaSDI: Parametric physics-informed greedy latent space dynamics identification.

Xiaolong He, Youngsoo Choi, William D. Fries, Jonathan L. Belof, Jiun-Shyan Chen

J. Comput. Phys., 2023

Weak-Form Latent Space Dynamics Identification.

April Tran, Xiaolong He, Daniel A. Messenger, Youngsoo Choi, David M. Bortz

CoRR, 2023

Data-Driven Modeling of an Unsaturated Bentonite Buffer Model Test Under High Temperatures Using an Enhanced Axisymmetric Reproducing Kernel Particle Method.

Jonghyuk Baek, Yanran Wang, Xiaolong He, Yu Lu, John S. McCartney, Jiun-Shyan Chen

CoRR, 2023

A Multi-Resolution Physics-Informed Recurrent Neural Network: Formulation and Application to Musculoskeletal Systems.

Karan Taneja, Xiaolong He, Qizhi He, Jiun-Shyan Chen

CoRR, 2023

2022

Thermodynamically Consistent Physics-Informed Data-Driven Computing and Reduced-Order Modeling of Nonlinear Materials

Xiaolong He

PhD thesis, 2022

Certified data-driven physics-informed greedy auto-encoder simulator.

Xiaolong He, Youngsoo Choi, William D. Fries, Jonathan L. Belof, Jiun-Shyan Chen

CoRR, 2022

Deep autoencoders for physics-constrained data-driven nonlinear materials modeling.

Xiaolong He, Qizhi He, Jiun-Shyan Chen

CoRR, 2022

Thermodynamically Consistent Machine-Learned Internal State Variable Approach for Data-Driven Modeling of Path-Dependent Materials.

Xiaolong He, Jiun-Shyan Chen

CoRR, 2022

LaSDI: Parametric Latent Space Dynamics Identification.

William Fries, Xiaolong He, Youngsoo Choi

CoRR, 2022

2021

Deep Autoencoders for Nonlinear Physics-Constrained Data-Driven Computational Framework with Application to Biological Tissue Modeling.

Xiaolong He, Qizhi He, Jiun-Shyan Chen

Proceedings of the AAAI 2021 Spring Symposium on Combining Artificial Intelligence and Machine Learning with Physical Sciences, Stanford, CA, USA, March 22nd - to, 2021