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Latent Evolution Operator (LEO): State-to-State Forecasting of Parametric PDEs
Solving time-dependent parametric partial differential equations (PDEs) with high-fidelity solvers is expensive in multi-query settings. This motivates reduced-order models in latent space. Existing methods are typically either (i) recurrent latent dynamics models, which require step-by-step integra
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