Bayesian Synthetic Likelihood

9 May 2023

Papers citing "Bayesian Synthetic Likelihood"

32 / 32 papers shown

Title
Stacking Variational Bayesian Monte Carlo Francesco Silvestrin Chengkun Li Luigi Acerbi BDL 32 0 0 07 Apr 2025
Misspecification-robust likelihood-free inference in high dimensions Owen Thomas Raquel Sá-Leao H. Lencastre Samuel Kaski J. Corander Henri Pesonen 66 9 0 17 Feb 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 108 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 58 13 0 03 Jan 2025
Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood Yuta Shikuri GP 30 0 0 23 Dec 2024
PQMass: Probabilistic Assessment of the Quality of Generative Models using Probability Mass Estimation Pablo Lemos Sammy N. Sharief Nikolay Malkin Laurence Perreault Levasseur Y. Hezaveh Laurence Perreault-Levasseur Yashar Hezaveh 19 3 0 06 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 16 0 0 30 Jan 2024
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference Pablo Lemos A. Coogan Y. Hezaveh Laurence Perreault Levasseur 27 30 0 06 Feb 2023
Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference Ryan P. Kelly David J. Nott David T. Frazier D. Warne Christopher C. Drovandi 20 10 0 31 Jan 2023
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 20 15 0 01 Aug 2022
Bayesian model calibration for block copolymer self-assembly: Likelihood-free inference and expected information gain computation via measure transport Ricardo Baptista Lianghao Cao Joshua Chen Omar Ghattas Fengyi Li Youssef M. Marzouk J. Oden 16 11 0 22 Jun 2022
Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization Lorenzo Pacchiardi Ritabrata Dutta TPM BDL UQCV GAN 11 18 0 31 May 2022
On predictive inference for intractable models via approximate Bayesian computation Marko Jarvenpaa J. Corander TPM 25 2 0 23 Mar 2022
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap Charita Dellaporta Jeremias Knoblauch Theodoros Damoulas F. Briol 18 42 0 09 Feb 2022
Population Calibration using Likelihood-Free Bayesian Inference Christopher C. Drovandi Brodie A. J. Lawson A. Jenner A. Browning 7 2 0 04 Feb 2022
Optimality in Noisy Importance Sampling F. Llorente Luca Martino Jesse Read D. Delgado 12 5 0 07 Jan 2022
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 27 25 0 20 Dec 2021
Multifidelity multilevel Monte Carlo to accelerate approximate Bayesian parameter inference for partially observed stochastic processes D. Warne Thomas P. Prescott Ruth Baker Matthew J. Simpson 12 15 0 26 Oct 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 17 74 0 15 Apr 2021
A Comparison of Likelihood-Free Methods With and Without Summary Statistics Christopher C. Drovandi David T. Frazier 19 33 0 03 Mar 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 15 33 0 12 Feb 2021
Likelihood-Free Inference with Deep Gaussian Processes Alexander Aushev Henri Pesonen Markus Heinonen J. Corander Samuel Kaski GP 11 10 0 18 Jun 2020
Variational Bayesian Monte Carlo with Noisy Likelihoods Luigi Acerbi 6 40 0 15 Jun 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 31 117 0 10 Feb 2020
Robust Optimisation Monte Carlo Borislav Ikonomov Michael U. Gutmann 9 8 0 01 Apr 2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments David T. Frazier David J. Nott Christopher C. Drovandi Robert Kohn 16 40 0 13 Feb 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 18 358 0 18 May 2018
Approximating the Likelihood in Approximate Bayesian Computation Christopher C. Drovandi Clara Grazian Kerrie Mengersen Christian P. Robert 16 12 0 18 Mar 2018
Flexible statistical inference for mechanistic models of neural dynamics Jan-Matthis Lueckmann P. J. Gonçalves Giacomo Bassetto Kaan Öcal M. Nonnenmacher Jakob H. Macke 14 240 0 06 Nov 2017
An automatic adaptive method to combine summary statistics in approximate Bayesian computation Jonathan U. Harrison R. Baker 17 17 0 07 Mar 2017
Bayesian inference for stochastic differential equation mixed effects models of a tumor xenography study Umberto Picchini J. Forman 24 23 0 09 Jul 2016
MCMC using Hamiltonian dynamics Radford M. Neal 132 3,263 0 09 Jun 2012