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Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models

14 January 2015

Papers citing "Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models"

26 / 26 papers shown

Title
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 232 9 0 17 Feb 2025
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 204 0 0 20 Jan 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 257 2 0 17 Jan 2025
A survey of Monte Carlo methods for noisy and costly densities with application to reinforcement learning and ABC F. Llorente Luca Martino Jesse Read D. Delgado OffRL 165 14 0 03 Jan 2025
Gaussian process modeling in approximate Bayesian computation to estimate horizontal gene transfer in bacteria Marko Jarvenpaa Michael U. Gutmann Aki Vehtari Pekka Marttinen 195 41 0 20 Oct 2016
High Dimensional Bayesian Optimisation and Bandits via Additive Models Kirthevasan Kandasamy J. Schneider Barnabás Póczós 82 356 0 05 Mar 2015
Scalable Bayesian Optimization Using Deep Neural Networks Jasper Snoek Oren Rippel Kevin Swersky Ryan Kiros N. Satish N. Sundaram Md. Mostofa Ali Patwary P. Prabhat Ryan P. Adams BDL UQCV 99 1,045 0 19 Feb 2015
Likelihood-free inference via classification Michael U. Gutmann Ritabrata Dutta Samuel Kaski J. Corander 216 63 0 18 Jul 2014
Student-t Processes as Alternatives to Gaussian Processes Amar Shah A. Wilson Zoubin Ghahramani GP 114 203 0 18 Feb 2014
GPS-ABC: Gaussian Process Surrogate Approximate Bayesian Computation Edward Meeds Max Welling 197 124 0 13 Jan 2014
Accelerating ABC methods using Gaussian processes Richard D. Wilkinson 115 109 0 07 Jan 2014
Gaussian Processes for Big Data J. Hensman Nicolò Fusi Neil D. Lawrence GP 113 1,236 0 26 Sep 2013
Parallel Gaussian Process Optimization with Upper Confidence Bound and Pure Exploration E. Contal David Buffoni Alexandre Robicquet Nicolas Vayatis 104 213 0 19 Apr 2013
Learning to Optimize Via Posterior Sampling Daniel Russo Benjamin Van Roy 236 703 0 11 Jan 2013
Joint Optimization and Variable Selection of High-dimensional Gaussian Processes Bo Chen R. Castro Andreas Krause GP 109 87 0 27 Jun 2012
Parallelizing Exploration-Exploitation Tradeoffs with Gaussian Process Bandit Optimization Thomas Desautels Andreas Krause J. W. Burdick 109 473 0 27 Jun 2012
Practical Bayesian Optimization of Machine Learning Algorithms Jasper Snoek Hugo Larochelle Ryan P. Adams 384 7,981 0 13 Jun 2012
A Family of Computationally Efficient and Simple Estimators for Unnormalized Statistical Models Miika Pihlaja Michael U. Gutmann Aapo Hyvarinen 89 45 0 15 Mar 2012
Bregman divergence as general framework to estimate unnormalized statistical models Michael U. Gutmann J. Hirayama 94 80 0 14 Feb 2012
Robust Kernel Density Estimation JooSeuk Kim Clayton D. Scott OOD 98 390 0 15 Jul 2011
Approximate Bayesian Computational methods Jean-Michel Marin Pierre Pudlo Christian P. Robert Robin J. Ryder 258 867 0 05 Jan 2011
A Tutorial on Bayesian Optimization of Expensive Cost Functions, with Application to Active User Modeling and Hierarchical Reinforcement Learning E. Brochu Vlad M. Cora Nando de Freitas GP 140 2,449 0 12 Dec 2010
Gaussian Process Optimization in the Bandit Setting: No Regret and Experimental Design Niranjan Srinivas Andreas Krause Sham Kakade Matthias Seeger 181 1,626 0 21 Dec 2009
Approximate Bayesian Computation: a nonparametric perspective M. Blum 222 240 0 03 Apr 2009
Approximate Bayesian computation scheme for parameter inference and model selection in dynamical systems Tina Toni David Welch N. Strelkowa Andreas Ipsen M. Stumpf 261 1,552 0 14 Jan 2009
Adaptive approximate Bayesian computation Mark Beaumont J. Cornuet Jean-Michel Marin Christian P. Robert 237 646 0 15 May 2008