A scalable framework for learning the geometry-dependent solution operators of partial differential equations.

Minglang Yin1,2, Nicolas Charon3, Ryan Brody1,4

  • 1Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA.

PubMed
Summary

This study introduces Diffeomorphic Mapping Operator Learning (DIMON), an AI framework for efficiently solving partial differential equations (PDEs) across diverse geometries. DIMON significantly reduces computational costs for complex simulations, from hours to seconds.

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