2 citations · 2 across the 5 of their papers we have counts for
6 papers
Energy Approach from -Graph to Continuum Diffusion Model with Connectivity Functional
Yahong Yang, Sun Lee, Jeff Calder +1
We derive an energy-based continuum limit for -graphs endowed with a general connectivity functional. We prove that the discrete energy and its continuum counterpart d…
An Imbalanced Learning-based Sampling Method for Physics-informed Neural Networks
Jiaqi Luo, Yahong Yang, Yuan Yuan +2
This paper introduces Residual-based Smote (RSmote), an innovative local adaptive sampling technique tailored to improve the performance of Physics-Informed Neural Networks (PINNs)…
Multiscale Neural Networks for Approximating Green's Functions
Wenrui Hao, Rui Peng Li, Yuanzhe Xi +2
Neural networks (NNs) have been widely used to solve partial differential equations (PDEs) in the applications of physics, biology, and engineering. One effective approach for solv…
On pattern formation in the thermodynamically-consistent variational Gray-Scott model
Wenrui Hao, Chun Liu, Yiwei Wang +1
In this paper, we explore pattern formation in a four-species variational Gary-Scott model, which includes all reverse reactions and introduces a virtual species to describe the bi…
Newton Informed Neural Operator for Computing Multiple Solutions of Nonlinear Partials Differential Equations
Wenrui Hao, Xinliang Liu, Yahong Yang
Solving nonlinear partial differential equations (PDEs) with multiple solutions using neural networks has found widespread applications in various fields such as physics, biology,…
Homotopy Relaxation Training Algorithms for Infinite-Width Two-Layer ReLU Neural Networks
Yahong Yang, Qipin Chen, Wenrui Hao
In this paper, we present a novel training approach called the Homotopy Relaxation Training Algorithm (HRTA), aimed at accelerating the training process in contrast to traditional…