Bayesian Synthetic Likelihood

9 May 2023

Papers citing "Bayesian Synthetic Likelihood"

50 / 107 papers shown

Title
Simulation-based inference for stochastic nonlinear mixed-effects models with applications in systems biology Henrik Häggström Sebastian Persson Marija Cvijovic Umberto Picchini 29 0 0 15 Apr 2025
Stacking Variational Bayesian Monte Carlo Francesco Silvestrin Chengkun Li Luigi Acerbi BDL 42 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 77 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 116 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 74 13 0 03 Jan 2025
Learning from Summarized Data: Gaussian Process Regression with Sample Quasi-Likelihood Yuta Shikuri GP 41 0 0 23 Dec 2024
Structured Regularization for Constrained Optimization on the SPD Manifold Andrew Cheng Melanie Weber 13 1 0 12 Oct 2024
Cost-aware Simulation-based Inference Ayush Bharti Daolang Huang Samuel Kaski F. Briol 36 1 0 10 Oct 2024
A Comprehensive Guide to Simulation-based Inference in Computational Biology Xiaoyu Wang Ryan P. Kelly A. Jenner D. Warne Christopher C. Drovandi 33 3 0 29 Sep 2024
A Likelihood-Free Approach to Goal-Oriented Bayesian Optimal Experimental Design Atlanta Chakraborty Xun Huan Tommie A. Catanach 37 3 0 18 Aug 2024
Ensemble Kalman inversion approximate Bayesian computation R. Everitt 29 0 0 26 Jul 2024
Preconditioned Neural Posterior Estimation for Likelihood-free Inference Xiaoyu Wang Ryan P. Kelly D. Warne Christopher C. Drovandi 37 4 0 21 Apr 2024
A Quadrature Approach for General-Purpose Batch Bayesian Optimization via Probabilistic Lifting Masaki Adachi Satoshi Hayakawa Martin Jørgensen Saad Hamid Harald Oberhauser Michael A. Osborne GP 32 3 0 18 Apr 2024
Using early rejection Markov chain Monte Carlo and Gaussian processes to accelerate ABC methods Xuefei Cao Shijia Wang Yongdao Zhou 36 3 0 13 Apr 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 29 3 0 06 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 34 0 0 30 Jan 2024
Stratified distance space improves the efficiency of sequential samplers for approximate Bayesian computation Henri Pesonen J. Corander 33 0 0 30 Dec 2023
Towards Data-Conditional Simulation for ABC Inference in Stochastic Differential Equations P. Jovanovski Andrew Golightly Umberto Picchini 20 1 0 16 Oct 2023
perms: Likelihood-free estimation of marginal likelihoods for binary response data in Python and R Dennis Christensen Per August Jarval Moen 11 0 0 04 Sep 2023
A transport approach to sequential simulation-based inference Paul-Baptiste Rubio Youssef Marzouk M. Parno 35 1 0 26 Aug 2023
Learning Robust Statistics for Simulation-based Inference under Model Misspecification Daolang Huang Ayush Bharti Amauri Souza Luigi Acerbi Samuel Kaski 46 30 0 25 May 2023
Wasserstein Gaussianization and Efficient Variational Bayes for Robust Bayesian Synthetic Likelihood Nhat-Minh Nguyen Minh-Ngoc Tran Christopher C. Drovandi David J. Nott 9 1 0 24 May 2023
Generalised likelihood profiles for models with intractable likelihoods D. Warne Oliver J. Maclaren E. Carr Matthew J. Simpson Christopher C. Drovandi 32 8 0 18 May 2023
JANA: Jointly Amortized Neural Approximation of Complex Bayesian Models Stefan T. Radev Marvin Schmitt Valentin Pratz Umberto Picchini Ullrich Kothe Paul-Christian Bürkner BDL 34 29 0 17 Feb 2023
Reliable Bayesian Inference in Misspecified Models David T. Frazier Robert Kohn Christopher C. Drovandi David Gunawan 16 3 0 13 Feb 2023
Sampling-Based Accuracy Testing of Posterior Estimators for General Inference Pablo Lemos A. Coogan Y. Hezaveh Laurence Perreault Levasseur 40 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 25 10 0 31 Jan 2023
Better Together: pooling information in likelihood-free inference David T. Frazier Christopher C. Drovandi David J. Nott 19 1 0 05 Dec 2022
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models Louis Sharrock J. Simons Song Liu Mark Beaumont DiffM 64 34 0 10 Oct 2022
Approximate Methods for Bayesian Computation Radu V. Craiu Evgeny Levi 15 5 0 06 Oct 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 35 15 0 01 Aug 2022
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
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 34 11 0 22 Jun 2022
Generalised Bayesian Inference for Discrete Intractable Likelihood Takuo Matsubara Jeremias Knoblauch F. Briol Chris J. Oates 27 14 0 16 Jun 2022
Likelihood-Free Inference with Generative Neural Networks via Scoring Rule Minimization Lorenzo Pacchiardi Ritabrata Dutta TPM BDL UQCV GAN 26 18 0 31 May 2022
pyABC: Efficient and robust easy-to-use approximate Bayesian computation Yannik Schälte Emmanuel Klinger Emad Alamoudi Jan Hasenauer 11 22 0 24 Mar 2022
On predictive inference for intractable models via approximate Bayesian computation Marko Jarvenpaa J. Corander TPM 33 2 0 23 Mar 2022
Modularized Bayesian analyses and cutting feedback in likelihood-free inference Atlanta Chakraborty David J. Nott Christopher C. Drovandi David T. Frazier Scott A. Sisson 33 14 0 18 Mar 2022
Weakly informative priors and prior-data conflict checking for likelihood-free inference Atlanta Chakraborty David J. Nott Michael Evans 22 4 0 21 Feb 2022
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap Charita Dellaporta Jeremias Knoblauch Theodoros Damoulas F. Briol 28 42 0 09 Feb 2022
Population Calibration using Likelihood-Free Bayesian Inference Christopher C. Drovandi Brodie A. J. Lawson A. Jenner A. Browning 17 2 0 04 Feb 2022
Black-box Bayesian inference for economic agent-based models Joel Dyer Patrick W Cannon J. Farmer Sebastian M. Schmon 18 23 0 01 Feb 2022
Optimality in Noisy Importance Sampling F. Llorente Luca Martino Jesse Read D. Delgado 39 5 0 07 Jan 2022
Efficient Multifidelity Likelihood-Free Bayesian Inference with Adaptive Computational Resource Allocation Thomas P. Prescott D. Warne R. Baker 24 6 0 22 Dec 2021
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 39 26 0 20 Dec 2021
Measuring the accuracy of likelihood-free inference Aden Forrow R. Baker 13 2 0 15 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 22 15 0 26 Oct 2021
A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful Joeri Hermans Arnaud Delaunoy François Rozet Antoine Wehenkel Volodimir Begy Gilles Louppe 64 38 0 13 Oct 2021
Validation and Inference of Agent Based Models D. Townsend AI4CE 14 2 0 08 Jul 2021