Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localisation

14 July 2022

Papers citing "Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localisation"

13 / 13 papers shown

Title
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 216 9 0 17 Feb 2025
Bayesian Synthetic Likelihood David T. Frazier Christopher C. Drovandi David J. Nott 175 220 0 09 May 2023
Truncated Marginal Neural Ratio Estimation Benjamin Kurt Miller A. Cole Patrick Forré Gilles Louppe Christoph Weniger 104 38 0 02 Jul 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 413 33 0 12 Feb 2021
Solving high-dimensional parameter inference: marginal posterior densities & Moment Networks N. Jeffrey Benjamin Dan Wandelt 64 39 0 11 Nov 2020
BayesFlow: Learning complex stochastic models with invertible neural networks Stefan T. Radev U. Mertens A. Voss Lynton Ardizzone Ullrich Kothe BDL 288 197 0 13 Mar 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 207 1,711 0 05 Dec 2019
Likelihood-free approximate Gibbs sampling G. S. Rodrigues David J. Nott Scott A. Sisson 49 25 0 11 Jun 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 384 330 0 17 May 2019
Adaptive Gaussian Copula ABC Yanzhi Chen Michael U. Gutmann TPM 149 27 0 27 Feb 2019
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 190 151 0 30 Nov 2016
The Rate of Convergence for Approximate Bayesian Computation Stuart Barber J. Voss M. Webster 61 80 0 08 Nov 2013
Non-linear regression models for Approximate Bayesian Computation M. Blum O. François 215 484 0 24 Sep 2008