mlsanityData to 13 Oct 2026

ABC Samplers

arXiv 1802.09650 ↗First posted 26 Feb 2018stat.CO stat.ME stat.MLcited by 2

Not on the map. Why?

Abstract (arXiv)

This Chapter, "ABC Samplers", is to appear in the forthcoming Handbook of Approximate Bayesian Computation (2018). It details the main ideas and algorithms used to sample from the ABC approximation to the posterior distribution, including methods based on rejection/importance sampling, MCMC and sequential Monte Carlo.

Key facts. Cited by 2 papers in the map (data through 13 Oct 2026). First posted on arXiv 26 Feb 2018.

Builds on

No reference list yet.

Built on by

Cited by year

Citing papers per year: 2022: 2.

2 papers.

  1. 2022Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrapcited by 41
  2. 2022Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localisationcited by 2