Search Results for author: Nicolas Nytko

Found 3 papers, 3 papers with code

Date Published Github Stars

MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods

1 code implementation • 26 Jan 2023 • Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman, Scott MacLachlan, Luke Olson, Matthew West

Domain decomposition methods (DDMs) are popular solvers for discretized systems of partial differential equations (PDEs), with one-level and multilevel variants.

2
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Code

Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation

1 code implementation • 10 Dec 2022 • Nicolas Nytko, Ali Taghibakhshi, Tareq Uz Zaman, Scott MacLachlan, Luke N. Olson, Matt West

Sparse matrix representations are ubiquitous in computational science and machine learning, leading to significant reductions in compute time, in comparison to dense representation, for problems that have local connectivity.

11
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Code

Learning Interface Conditions in Domain Decomposition Solvers

1 code implementation • 19 May 2022 • Ali Taghibakhshi, Nicolas Nytko, Tareq Zaman, Scott MacLachlan, Luke Olson, Matthew West

Domain decomposition methods are widely used and effective in the approximation of solutions to partial differential equations.

3
Paper
Code
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