A physics-driven neural operator with latent generative encoding solves forward and inverse PDE problems without labeled data, using weak-form residuals to handle discontinuous coefficients.
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DGenNO: A Novel Physics-aware Neural Operator for Solving Forward and Inverse PDE Problems based on Deep, Generative Probabilistic Modeling
A physics-driven neural operator with latent generative encoding solves forward and inverse PDE problems without labeled data, using weak-form residuals to handle discontinuous coefficients.