A physics-informed convolutional neural operator predicts scattered Helmholtz wavefields with up to 53% lower relative error than its purely data-driven counterpart on held-out velocity models.
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An effective physics-informed neural operator framework for predicting wavefields
A physics-informed convolutional neural operator predicts scattered Helmholtz wavefields with up to 53% lower relative error than its purely data-driven counterpart on held-out velocity models.