Learning Interface Conditions in Domain Decomposition Solvers. - Ali Taghibakhshi; Nicolas Nytko; Tareq Uz Zaman; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (NeurIPS, 2022)

Optimized Sparse Matrix Operations for Reverse Mode Automatic Differentiation. - Nicolas Nytko; Ali Taghibakhshi; Tareq-Uz-Zaman; Scott P. MacLachlan; Luke N. Olson; Matt West 001 (CoRR, 2022)

MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods. - Ali Taghibakhshi; Nicolas Nytko; Tareq Uz Zaman; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (ICML, 2023)

Generalizing Lloyd's Algorithm for Graph Clustering. - Tareq Uz Zaman; Nicolas Nytko; Ali Taghibakhshi; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (SIAM J. Sci. Comput., 2024)

Generalizing reduction-based algebraic multigrid. - Tareq Uz Zaman; Nicolas Nytko; Ali Taghibakhshi; Scott P. MacLachlan; Luke N. Olson; Matthew West 001 (Numer. Linear Algebra Appl., 2024)

Teaching An Old Dog New Tricks: Porting Legacy Code to Heterogeneous Compute Architectures With Automated Code Translation. - Nicolas Nytko; Andrew Reisner; J. David Moulton; Luke N. Olson; Matthew West 001 (CoRR, 2025)