3 papers
stat.ML2025
Gaussian process surrogate with physical law-corrected prior for multi-coupled PDEs defined on irregular geometry
Pucheng Tang, Hongqiao Wang, Wenzhou Lin +2
Parametric partial differential equations (PDEs) serve as fundamental mathematical tools for modeling complex physical phenomena, yet repeated high-fidelity numerical simulations a…
stat.ML2025
Accelerated Bayesian Optimal Experimental Design via Conditional Density Estimation and Informative Data
Miao Huang, Hongqiao Wang, Kunyu Wu
The Design of Experiments (DOEs) is a fundamental scientific methodology that provides researchers with systematic principles and techniques to enhance the validity, reliability, a…
stat.ME2024
Simulation-based transition density approximation for the inference of SDE models
Xin Cai, Jingyu Yang, Zhibao Li +2
Stochastic Differential Equations (SDEs) serve as a powerful modeling tool in various scientific domains, including systems science, engineering, and ecological science. While the…