2 citations · 2 across the 3 of their papers we have counts for
3 papers
math.NA2022
Neural Networks with Local Converging Inputs (NNLCI) for Solving Conservation Laws, Part II: 2D Problems
Haoxiang Huang, Yingjie Liu, Vigor Yang
In our prior work [arXiv:2109.09316], neural network methods with inputs based on domain of dependence and a converging sequence were introduced for solving one dimensional conserv…
math.NA2021★ 2 cited
Neural Networks with Inputs Based on Domain of Dependence and A Converging Sequence for Solving Conservation Laws, Part I: 1D Riemann Problems
Haoxiang Huang, Yingjie Liu, Vigor Yang
Recent research works for solving partial differential equations (PDEs) with deep neural networks (DNNs) have demonstrated that spatiotemporal function approximators defined by aut…
math.AP2017
A Methodology for Projection-Based Model Reduction with Black-Box High-Fidelity Models
S. Ashwin Renganathan, Yingjie Liu, Dimitri N. Mavris
This paper presents a methodology that enables projection-based model reduction for black-box high-fidelity models such as commercial CFD codes. The methodology specifically addres…