Luke Olson

4 papers · 2021–2024 · 2 venues · across top CS/AI venues

Authors are matched by name, so researchers who share a name ("Yang Liu", "Wei Wang") appear as a single profile and their paper counts, venues and achievements are combined. How identity is handled.

Achievements

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🌍 Conference Polyglot · Bronze 🌉 Interdisciplinary Bridge · Bronze 🗺️ Taxonomy Completionist (10)

Venues

ICML (2) NeurIPS (2)

Top co-authors

Matthew West (4) Ali Taghibakhshi (3) Scott MacLachlan (3) Nicolas Nytko (2) Tareq Uz Zaman (2) Ehsan Saleh (1) Tim Bretl (1) Saba Ghaffari (1)

Research topics

Machine Learning (4) Deep Learning (3) Architectures (3) Optimization & Theory (3) Mathematics & Optimization (2) Mathematics (2) Artificial Intelligence (1) Reinforcement Learning (1) Applications (1) Core AI (1) Core Methods (1) Learning Types (1) Techniques (1)

Keywords

graph neural network (2) domain decomposition (2) partial differential equation (2) physics-informed neural network (1) loss function (1) linear system solver (1) graph coarsening (1) deterministic sampling (1) multilevel method (1) unsupervised loss (1) unstructured grid (1) graph convolutional neural network (1) algebraic multigrid (1) domain decomposition method (1) optimized schwarz method (1) multigrid method (1) unsupervised loss function (1) linear solver (1) schwarz method (1) delayed target method (1)

Papers

Learning from Integral Losses in Physics Informed Neural Networks ICML 2024 MG-GNN: Multigrid Graph Neural Networks for Learning Multilevel Domain Decomposition Methods ICML 2023 Learning Interface Conditions in Domain Decomposition Solvers NeurIPS 2022 Optimization-Based Algebraic Multigrid Coarsening Using Reinforcement Learning NeurIPS 2021