May 5, 2024 · To resolve this problem, we propose a non-intrusive methodology with a novel gradient estimation technique to combine machine learning and ...
This paper formulates a general framework to describe these problems, and proposes a gradient-based algorithm to solve them in a unified way, ...
As an illustration of this approach, we study the adaptive generation of parameters for iterative solvers to accelerate the solution of differential equations.
In Section 2, we propose a general framework, called gradient-based meta-solving, to analyze and develop learning-based numerical methods. Using the frame-.
Jan 28, 2022 · In this paper, we tackle this issue by formulating a general framework to describe these problems, and propose a gradient-based algorithm to ...
Missing: Accelerating | Show results with:Accelerating
This paper proposes a framework to analyze learning-based acceleration approaches of iterative methods, where one can immediately identify a departure from ...
The overall architecture of non-intrusive gradient-based meta-solving. Algorithm 1 Non-intrusive gradient-based meta-solving. Input: (P, T ): task space, Ψ: ...
Jun 17, 2022 · In this paper, we propose a framework to analyze such learning-based acceleration approaches, where one can immediately identify a departure ...
Missing: solving. | Show results with:solving.
Oct 27, 2021 · PDF | Meta Learning has been in focus in recent years due to the meta-learner model's ability to adapt well and generalize to new tasks, ...
Missing: numerical | Show results with:numerical
To resolve this problem, we propose a non-intrusive methodology with a novel gradient estimation technique to combine machine learning and legacy numerical ...