Adaptive Gaussian Copula ABC

27 February 2019

Papers citing "Adaptive Gaussian Copula ABC"

18 / 18 papers shown

Title
Copula Approximate Bayesian Computation Using Distribution Random Forests G. Karabatsos 44 1 0 28 Feb 2024
An Extendable Python Implementation of Robust Optimisation Monte Carlo Vasilis Gkolemis Michael U. Gutmann Henri Pesonen 15 1 0 19 Sep 2023
Improving the Accuracy of Marginal Approximations in Likelihood-Free Inference via Localisation Christopher C. Drovandi David J. Nott David T. Frazier 69 5 0 14 Jul 2022
Guided sequential ABC schemes for intractable Bayesian models Umberto Picchini M. Tamborrino 61 8 0 24 Jun 2022
Unifying Likelihood-free Inference with Black-box Optimization and Beyond Dinghuai Zhang Jie Fu Yoshua Bengio Aaron Courville 38 13 0 06 Oct 2021
Likelihood-Free Frequentist Inference: Bridging Classical Statistics and Machine Learning for Reliable Simulator-Based Inference Niccolò Dalmasso Luca Masserano David Y. Zhao Rafael Izbicki Ann B. Lee 30 5 0 08 Jul 2021
Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds Steven Kleinegesse Michael U. Gutmann FedML 33 25 0 10 May 2021
Fast ABC with joint generative modelling and subset simulation Eliane Maalouf D. Ginsbourger N. Linde 35 0 0 16 Apr 2021
Extending the statistical software package Engine for Likelihood-Free Inference Vasileios Gkolemis Michael U. Gutmann 10 0 0 08 Nov 2020
Neural Approximate Sufficient Statistics for Implicit Models Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 30 79 0 20 Oct 2020
Adversarial Likelihood-Free Inference on Black-Box Generator Dongjun Kim Weonyoung Joo Seung-Jae Shin Kyungwoo Song Il-Chul Moon GAN 11 4 0 13 Apr 2020
Sequential Bayesian Experimental Design for Implicit Models via Mutual Information Steven Kleinegesse Christopher C. Drovandi Michael U. Gutmann 16 28 0 20 Mar 2020
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting Niccolò Dalmasso Rafael Izbicki Ann B. Lee 17 20 0 24 Feb 2020
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse Michael U. Gutmann 26 66 0 19 Feb 2020
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 24 44 0 29 Oct 2019
Conditional Density Estimation Tools in Python and R with Applications to Photometric Redshifts and Likelihood-Free Cosmological Inference Niccolò Dalmasso T. Pospisil Ann B. Lee Rafael Izbicki P. Freeman A. Malz 11 41 0 30 Aug 2019
Robust Optimisation Monte Carlo Borislav Ikonomov Michael U. Gutmann 14 8 0 01 Apr 2019
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 42 145 0 30 Nov 2016