most citedLearning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers

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cs.LG2024

ConDiff: A Challenging Dataset for Neural Solvers of Partial Differential Equations

Vladislav Trifonov, Alexander Rudikov, Oleg Iliev +3

We present ConDiff, a novel dataset for scientific machine learning. ConDiff focuses on the parametric diffusion equation with space dependent coefficients, a fundamental problem i…

cs.LG2024★ 2 cited

Learning from Linear Algebra: A Graph Neural Network Approach to Preconditioner Design for Conjugate Gradient Solvers

Vladislav Trifonov, Alexander Rudikov, Oleg Iliev +3

Large linear systems are ubiquitous in modern computational science and engineering. The main recipe for solving them is the use of Krylov subspace iterative methods with well-desi…