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arXiv Machine Learning By Divyavardhan Singh, Dimple Sonone, Hammad Mohammad, Kishor Upla

SPARC-Net: A Spectral, Causality-Aware, and Hard-Constrained Physics-Informed Architecture for Stiff and Shock-Dominated Partial Differential Equations

Read the original on arXiv Machine Learning →

arXiv:2607. 11310v1 Announce Type: new Abstract: Physics-Informed Neural Networks (PINNs) provide a meshless approach for solving partial differential equations (PDEs), but suffer severe degradation in stiff and shock-dominated problems, where small PDE residuals can correspond to globally inaccurate solutions.

Summary generated by The Flow from the publisher's feed. The full article lives at arXiv Machine Learning.

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