6 citations · 11 across the 7 of their papers we have counts for
3 papers · 1 filter
MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods
Ali Taghibakhshi, Nicolas Nytko, Tareq Uz Zaman +3
Domain decomposition methods (DDMs) are popular solvers for discretized systems of partial differential equations (PDEs), with one-level and multilevel variants. These solvers rely…
Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation
Nicolas Nytko, Ali Taghibakhshi, Tareq Uz Zaman +3
Sparse matrix representations are ubiquitous in computational science and machine learning, leading to significant reductions in compute time, in comparison to dense representation…
Learning Interface Conditions in Domain Decomposition Solvers
Ali Taghibakhshi, Nicolas Nytko, Tareq Zaman +3
Domain decomposition methods are widely used and effective in the approximation of solutions to partial differential equations. Yet the optimal construction of these methods requir…