2 citations · 3 across the 2 of their papers we have counts for
4 papers
A Physics-Informed Neural Network Framework For Partial Differential Equations on 3D Surfaces: Time-Dependent Problems
Zhiwei Fang, Justin Zhang, Xiu Yang
In this paper, we show a physics-informed neural network solver for the time-dependent surface PDEs. Unlike the traditional numerical solver, no extension of PDE and mesh on the su…
Multifidelity Data Fusion via Gradient-Enhanced Gaussian Process Regression
Yixiang Deng, Guang Lin, Xiu Yang
We propose a data fusion method based on multi-fidelity Gaussian process regression (GPR) framework. This method combines available data of the quantity of interest (QoI) and its g…
Nonnegativity-Enforced Gaussian Process Regression
Andrew Pensoneault, Xiu Yang, Xueyu Zhu
Gaussian Process (GP) regression is a flexible non-parametric approach to approximate complex models. In many cases, these models correspond to processes with bounded physical prop…
When Bifidelity Meets CoKriging: An Efficient Physics-Informed Multifidelity Method
Xiu Yang, Xueyu Zhu, Jing Li
In this work, we propose a framework that combines the approximation-theory-based multifidelity method and Gaussian-process-regression-based multifidelity method to achieve data-mo…