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arXiv Machine Learning By Joseph Webb, Sadok Jerad, Coralia Cartis

An Optimisation Framework for the Well-Conditioned Training of Physics-Informed Neural Networks

Read the original on arXiv Machine Learning →

arXiv:2607. 02194v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) have emerged as a promising route to solve partial differential equations, yet they have struggled to reach the precision of classical solvers.

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

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