Optimization Monte Carlo: Efficient and Embarrassingly Parallel
Likelihood-Free Inference

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Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference

11 June 2015

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Papers citing "Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference"

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Title
An Extendable Python Implementation of Robust Optimisation Monte Carlo Vasilis Gkolemis Michael U. Gutmann Henri Pesonen 44 1 0 19 Sep 2023
Randomized Maximum Likelihood via High-Dimensional Bayesian Optimization Valentin Breaz Richard D. Wilkinson 65 0 0 17 Apr 2022
Sequential Bayesian Experimental Design for Implicit Models via Mutual Information Steven Kleinegesse Christopher C. Drovandi Michael U. Gutmann 149 28 0 20 Mar 2020
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 266 857 0 04 Nov 2019
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 100 47 0 29 Oct 2019
Likelihood-free approximate Gibbs sampling G. S. Rodrigues David J. Nott Scott A. Sisson 81 25 0 11 Jun 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 552 370 0 18 May 2018
Anytime Monte Carlo Lawrence M. Murray Sumeetpal S. Singh Anthony Lee 98 6 0 10 Dec 2016
A rare event approach to high dimensional Approximate Bayesian computation D. Prangle R. Everitt T. Kypraios 92 22 0 08 Nov 2016
Automatic Variational ABC Alexander Moreno T. Adel Edward Meeds James M. Rehg Max Welling 171 12 0 28 Jun 2016
Asymptotically exact inference in differentiable generative models Matthew M. Graham Amos J. Storkey BDL 189 33 0 25 May 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 200 158 0 20 May 2016