Search Results for author: Ketan Mittal

Found 2 papers, 1 papers with code

Multi-Agent Reinforcement Learning for Adaptive Mesh Refinement

1 code implementation • 2 Nov 2022 • Jiachen Yang, Ketan Mittal, Tarik Dzanic, Socratis Petrides, Brendan Keith, Brenden Petersen, Daniel Faissol, Robert Anderson

Comprehensive experiments show that VDGN policies significantly outperform error threshold-based policies in global error and cost metrics.

Multi-agent Reinforcement Learning reinforcement-learning +1

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Reinforcement Learning for Adaptive Mesh Refinement

no code implementations • 1 Mar 2021 • Jiachen Yang, Tarik Dzanic, Brenden Petersen, Jun Kudo, Ketan Mittal, Vladimir Tomov, Jean-Sylvain Camier, Tuo Zhao, Hongyuan Zha, Tzanio Kolev, Robert Anderson, Daniel Faissol

Large-scale finite element simulations of complex physical systems governed by partial differential equations (PDE) crucially depend on adaptive mesh refinement (AMR) to allocate computational budget to regions where higher resolution is required.

Inductive Bias reinforcement-learning +1

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