ABC
Approximate Bayesian Computation
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.](https://www.umass.edu/nanofabrics/sites/default/files/PDF_0.pdf)
Accelerating Simulation-based Inference with Emerging AI Hardware
https://paperswithcode.com/paper/accelerating-simulation-based-inference-with
Accelerating Simulation-based Inference with Emerging AI Hardware