Derivative-fidelity failure mode in physics-informed neural networks shown by function-value training benchmarks
Read the original at arxiv.org→arXiv:2609.13171v1 Announce Type: new Abstract: Physics-informed neural networks (PINNs) use automatic differentiation to impose differential-equation residuals, but good agreement in function values does not...
Original headline: "A derivative-fidelity failure mode in physics-informed neural networks: strengthened benchmark evidence from function-value training"
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- Sep 15, 04:00 UTC arXiv cs.LG lead source A derivative-fidelity failure mode in physics-informed neural networks: strengthened benchmark evidence from function-value training