2026
Error-Driven Graph Augmentation for Mesh-Based PDE Surrogates
ICML 2026poster
Graph Neural Networks (GNNs) on meshes have emerged as promising surrogates for computational mechanics, but standard local message passing struggles to propagate information across unstructured meshes, leading to large errors in regions with complex physics (e.g., shocks, wakes, boundary layers). E…