A nonconforming dual-mixed scheme for generalized Darcy-Forchheimer flow converges under low regularity via novel broken-space trace inequalities and yields optimal error estimates when extra smoothness is assumed.
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A convergent deep splitting scheme approximates the nonlinear filtering density via Fokker-Planck prediction and exact Bayesian update, with sampling to address high dimensions.
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A nonconforming method for a generalized Darcy-Forchheimer model
A nonconforming dual-mixed scheme for generalized Darcy-Forchheimer flow converges under low regularity via novel broken-space trace inequalities and yields optimal error estimates when extra smoothness is assumed.
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A convergent scheme for the Bayesian filtering problem based on the Fokker--Planck equation and deep splitting
A convergent deep splitting scheme approximates the nonlinear filtering density via Fokker-Planck prediction and exact Bayesian update, with sampling to address high dimensions.