A derivative-free ensemble Kalman-Bucy smoother is developed for continuous-time data assimilation that supports Bayesian causal inference and iterative model structure identification with small ensemble sizes under partial observations.
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Computational searches maximizing LPS integrals and L3 norms in 3D periodic Navier-Stokes flows found no evidence of singularity formation, but quantified close approaches and transient growth.
Gaussian primitives compress 3D Taylor-Green vortex flows at ratios over 1000x while preserving velocity but degrading enstrophy, with anisotropic extensions recovering small-scale vortical structures better than baseline or other variants.
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A Continuous-Time Ensemble Kalman-Bucy Smoother for Causal Inference and Model Discovery
A derivative-free ensemble Kalman-Bucy smoother is developed for continuous-time data assimilation that supports Bayesian causal inference and iterative model structure identification with small ensemble sizes under partial observations.
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The Ladyzhenskaya-Prodi-Serrin Conditions and the Search for Extreme Behavior in 3D Navier-Stokes Flows
Computational searches maximizing LPS integrals and L3 norms in 3D periodic Navier-Stokes flows found no evidence of singularity formation, but quantified close approaches and transient growth.
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Gaussian Field Representations for Turbulent Flow: Compression, Scale Separation, and Physical Fidelity
Gaussian primitives compress 3D Taylor-Green vortex flows at ratios over 1000x while preserving velocity but degrading enstrophy, with anisotropic extensions recovering small-scale vortical structures better than baseline or other variants.