Optimization Monte Carlo reformulates stochastic simulator inference as gradient-based deterministic optimization for faster, accurate posterior estimation in high-dimensional or challenging settings.
For a more detailed view, Figures 9 (Sbase), 10 (S dist base), 11 (SMoG), and 12 (S dist MoG ) report the meanC2ST score for each method across all dimensionalities and budgets
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Fast and Robust Simulation-Based Inference With Optimization Monte Carlo
Optimization Monte Carlo reformulates stochastic simulator inference as gradient-based deterministic optimization for faster, accurate posterior estimation in high-dimensional or challenging settings.