4 papers
Kernel-learning parameter prediction and evaluation in algebraic multigrid method for several PDEs
Junyue Luo, Xiaoqiang Yue, Fangfang Zhang +1
This paper explores the application of kernel learning methods for parameter prediction and evaluation in the Algebraic Multigrid Method (AMG), focusing on several Partial Differen…
From Model Choice to Model Belief: Establishing a New Measure for LLM-Based Research
Hongshen Sun, Juanjuan Zhang
Large language models (LLMs) are increasingly used to simulate human behavior, but common practices to use LLM-generated data are inefficient. Treating an LLM's output ("model choi…
Convergent analysis of algebraic multigrid method with data-driven parameter learning for non-selfadjoint elliptic problems
Juan Zhang, Junyue Luo
In this paper, we apply the practical GADI-HS iteration as a smoother in algebraic multigrid (AMG) method for solving second-order non-selfadjoint elliptic problem. Additionally, w…
Data-driven Model Reduction for Parameter-Dependent Matrix Equations via Operator Inference
Xuelian Wen, Qiuqi Li, Juan Zhang
This work develops a non-intrusive, data-driven surrogate modeling framework based on Operator Inference (OpInf) for rapidly solving parameter-dependent matrix equations in many-qu…