A framework that propagates full probability densities through random iteration equations, avoiding pathwise Monte Carlo, is demonstrated on ODEs, SDEs, optimization, and chaotic maps, but relies on an unquantified artificial-noise regularization.
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A Full-Density Approach to Simulating Random Iteration Equations with Applications
A framework that propagates full probability densities through random iteration equations, avoiding pathwise Monte Carlo, is demonstrated on ODEs, SDEs, optimization, and chaotic maps, but relies on an unquantified artificial-noise regularization.