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Parameterized Temporal Extrapolation of PDEs via Disentangled Latent Dynamics Manifold Fusion
Generalizing neural surrogate models across different PDE parameters remains difficult because changes in PDE coefficients often make learning harder and optimization less stable. The problem becomes even more severe when the model must also predict beyond the training time range. Existing methods u
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