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

v1v2 (latest)

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

11 June 2015

ArXiv (abs)PDF HTML

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

9 / 9 papers shown

Title
Sequential Monte Carlo with Adaptive Weights for Approximate Bayesian Computation Fernando V. Bonassi M. West 229 73 0 26 Mar 2015
Hamiltonian ABC Edward Meeds R. Leenders Max Welling BDL 160 31 0 06 Mar 2015
Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC Sungjin Ahn Anoop Korattikara Balan Nathan Liu Suju Rajan Max Welling BDL 90 59 0 05 Mar 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models Michael U. Gutmann J. Corander 157 288 0 14 Jan 2015
Asynchronous Anytime Sequential Monte Carlo Brooks Paige Frank Wood Arnaud Doucet Yee Whye Teh 43 47 0 10 Jul 2014
On Bayesian inference for the M/G/1 queue with efficient MCMC sampling Alexander Y. Shestopaloff Radford M. Neal 163 22 0 22 Jan 2014
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 359 7,954 0 13 Jun 2012
Non-linear regression models for Approximate Bayesian Computation M. Blum O. François 215 484 0 24 Sep 2008
Adaptive approximate Bayesian computation Mark Beaumont J. Cornuet Jean-Michel Marin Christian P. Robert 203 646 0 15 May 2008