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2000년 도입 · 논문 131편에서 사용

Class of methods in Bayesian Statistics where the posterior distribution is approximated over a rejection scheme on simulations because the likelihood function is intractable. Different parameters get sampled and simulated. Then a distance function is calculated to measure the quality of the simulation compared to data from real observations. Only simulations that fall below a certain threshold get accepted. Image source: Kulkarni et al.

출처: Accelerating Simulation-based Inference with Emerging AI Hardware

소개 논문: Accelerating Simulation-based Inference with Emerging AI Hardware