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Found 3 papers, 1 papers with code
Accelerating Legacy Numerical Solvers by Non-intrusive Gradient-based Meta-solving
Scientific computing is an essential tool for scientific discovery and engineering design, and its computational cost is always a main concern in practice.
Principled Acceleration of Iterative Numerical Methods Using Machine Learning
Iterative methods are ubiquitous in large-scale scientific computing applications, and a number of approaches based on meta-learning have been recently proposed to accelerate them.
Gradient-based Meta-solving and Its Applications to Iterative Methods for Solving Differential Equations
In science and engineering applications, it is often required to solve similar computational problems repeatedly.
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