PDYffusion combines PDE-regularized diffusion interpolation with UKF-based uncertainty-aware forecasting to deliver more stable and accurate long-horizon dynamical predictions than standard approaches.
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Lipschitz stability holds for low-rank unknowns in the fully nonlinear inverse medium scattering problem, with an ensemble Kalman filter proposed for iterative reconstruction whose dimension is set by the wave number.
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PDE-regularized Dynamics-informed Diffusion with Uncertainty-aware Filtering for Long-Horizon Dynamics
PDYffusion combines PDE-regularized diffusion interpolation with UKF-based uncertainty-aware forecasting to deliver more stable and accurate long-horizon dynamical predictions than standard approaches.
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Low-rank-assisted inverse medium scattering: Lipschiz stability and ensemble Kalman filter
Lipschitz stability holds for low-rank unknowns in the fully nonlinear inverse medium scattering problem, with an ensemble Kalman filter proposed for iterative reconstruction whose dimension is set by the wave number.