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20192025
most citedA randomized Newton's method for solving differential equations based on the neural network discretization

2 citations · 6 across the 7 of their papers we have counts for

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3 papers · 1 filter

math.NA2025

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…

cs.LG2025★ 1 cited

Learn Singularly Perturbed Solutions via Homotopy Dynamics

Chuqi Chen, Yahong Yang, Yang Xiang +1

Solving partial differential equations (PDEs) using neural networks has become a central focus in scientific machine learning. Training neural networks for singularly perturbed pro…

cs.LG2025

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)…