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20142026
most citedPhysics-informed graph neural Galerkin networks: A unified framework for solving PDE-governed forward and inverse problems

313 citations · 704 across the 32 of their papers we have counts for

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cs.CE2026

Feature tracking in physics-informed neural networks via joint optimization of nonlinear deformation manifolds: application to shocks

Akshay Thakur, Matthew Zahr

Physics-informed neural networks (PINNs) often converge to inaccurate solutions for conservation laws with shocks, because uniformly distributed collocation points undersample loca…