Bayesian Synthetic Likelihood

9 May 2023

Papers citing "Bayesian Synthetic Likelihood"

50 / 107 papers shown

Title
Warped Gradient-Enhanced Gaussian Process Surrogate Models for Exponential Family Likelihoods with Intractable Normalizing Constants Quan Vu M. Moores A. Zammit‐Mangion 20 1 0 10 May 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 27 74 0 15 Apr 2021
Approximate Bayesian inference from noisy likelihoods with Gaussian process emulated MCMC Marko Jarvenpaa J. Corander 8 3 0 08 Apr 2021
Synthetic Likelihood in Misspecified Models: Consequences and Corrections David T. Frazier Christopher C. Drovandi David J. Nott 23 10 0 08 Apr 2021
Metropolis-Hastings via Classification Tetsuya Kaji Veronika Rockova 23 8 0 06 Mar 2021
A Comparison of Likelihood-Free Methods With and Without Summary Statistics Christopher C. Drovandi David T. Frazier 34 33 0 03 Mar 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 34 33 0 12 Feb 2021
Score Matched Neural Exponential Families for Likelihood-Free Inference Lorenzo Pacchiardi Ritabrata Dutta 27 27 0 20 Dec 2020
On a Variational Approximation based Empirical Likelihood ABC Method S. Chaudhuri Subhro Ghosh David J. Nott Kim Cuc Pham 16 2 0 12 Nov 2020
Robust Approximate Bayesian Computation: An Adjustment Approach David T. Frazier Christopher C. Drovandi Rubén Loaiza-Maya 11 13 0 07 Aug 2020
Robust Bayesian Classification Using an Optimistic Score Ratio Viet Anh Nguyen Nian Si Jose H. Blanchet 19 13 0 08 Jul 2020
Transformations in Semi-Parametric Bayesian Synthetic Likelihood Jacob W. Priddle Christopher C. Drovandi 6 2 0 03 Jul 2020
Distortion estimates for approximate Bayesian inference Hanwen Xing Geoff K. Nicholls J. Lee 8 7 0 19 Jun 2020
Likelihood-Free Inference with Deep Gaussian Processes Alexander Aushev Henri Pesonen Markus Heinonen J. Corander Samuel Kaski GP 26 10 0 18 Jun 2020
Variational Bayesian Monte Carlo with Noisy Likelihoods Luigi Acerbi 22 40 0 15 Jun 2020
Computing Bayes: Bayesian Computation from 1763 to the 21st Century G. Martin David T. Frazier Christian P. Robert 42 17 0 14 Apr 2020
Adversarial Likelihood-Free Inference on Black-Box Generator Dongjun Kim Weonyoung Joo Seung-Jae Shin Kyungwoo Song Il-Chul Moon GAN 6 4 0 13 Apr 2020
An approximate KLD based experimental design for models with intractable likelihoods Ziqiao Ao Jinglai Li 11 5 0 01 Apr 2020
Sequential Bayesian Experimental Design for Implicit Models via Mutual Information Steven Kleinegesse Christopher C. Drovandi Michael U. Gutmann 8 28 0 20 Mar 2020
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting Niccolò Dalmasso Rafael Izbicki Ann B. Lee 9 20 0 24 Feb 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 45 117 0 10 Feb 2020
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 24 44 0 29 Oct 2019
Optimistic Distributionally Robust Optimization for Nonparametric Likelihood Approximation Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh Man-Chung Yue Daniel Kuhn W. Wiesemann 11 29 0 23 Oct 2019
Calculating Optimistic Likelihoods Using (Geodesically) Convex Optimization Viet Anh Nguyen Soroosh Shafieezadeh-Abadeh Man-Chung Yue Daniel Kuhn W. Wiesemann 8 23 0 17 Oct 2019
Batch simulations and uncertainty quantification in Gaussian process surrogate approximate Bayesian computation Marko Jarvenpaa Aki Vehtari Pekka Marttinen 25 15 0 14 Oct 2019
Efficient Bayesian synthetic likelihood with whitening transformations Jacob W. Priddle Scott A. Sisson David T. Frazier Christopher C. Drovandi 16 18 0 11 Sep 2019
A review of Approximate Bayesian Computation methods via density estimation: inference for simulator-models C. Grazian Yanan Fan TPM 19 22 0 06 Sep 2019
Marginally-calibrated deep distributional regression Nadja Klein David J. Nott M. Smith UQCV 32 14 0 26 Aug 2019
Particle Methods for Stochastic Differential Equation Mixed Effects Models Imke Botha Robert Kohn Christopher C. Drovandi 17 21 0 25 Jul 2019
BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic Likelihood Ziwen An Leah F. South Christopher C. Drovandi 16 11 0 25 Jul 2019
Efficient inference for stochastic differential equation mixed-effects models using correlated particle pseudo-marginal algorithms Samuel Wiqvist Andrew Golightly Ashleigh T. McLean Umberto Picchini 11 1 0 23 Jul 2019
Ensemble MCMC: Accelerating Pseudo-Marginal MCMC for State Space Models using the Ensemble Kalman Filter Christopher C. Drovandi R. Everitt Andrew Golightly D. Prangle 14 13 0 05 Jun 2019
Validation of Approximate Likelihood and Emulator Models for Computationally Intensive Simulations Niccolò Dalmasso Ann B. Lee Rafael Izbicki T. Pospisil Ilmun Kim Chieh-An Lin 24 8 0 27 May 2019
Stratified sampling and bootstrapping for approximate Bayesian computation Umberto Picchini R. Everitt 14 1 0 20 May 2019
Finding our Way in the Dark: Approximate MCMC for Approximate Bayesian Methods Evgeny Levi Radu V. Craiu 14 6 0 16 May 2019
Parallel Gaussian process surrogate Bayesian inference with noisy likelihood evaluations Marko Jarvenpaa Michael U. Gutmann Aki Vehtari Pekka Marttinen 16 40 0 03 May 2019
Robust Approximate Bayesian Inference with Synthetic Likelihood David T. Frazier Christopher C. Drovandi 18 44 0 09 Apr 2019
Robust Optimisation Monte Carlo Borislav Ikonomov Michael U. Gutmann 14 8 0 01 Apr 2019
Bayesian Learning of Conditional Kernel Mean Embeddings for Automatic Likelihood-Free Inference Kelvin Hsu F. Ramos 30 12 0 03 Mar 2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments David T. Frazier David J. Nott Christopher C. Drovandi Robert Kohn 23 40 0 13 Feb 2019
Dynamic Likelihood-free Inference via Ratio Estimation (DIRE) Traiko Dinev Michael U. Gutmann 8 27 0 23 Oct 2018
An easy-to-use empirical likelihood ABC method S. Chaudhuri Subhro Ghosh David J. Nott Kim Cuc Pham 28 6 0 03 Oct 2018
Robust Bayesian Synthetic Likelihood via a Semi-Parametric Approach Ziwen An David J. Nott Christopher C. Drovandi 18 51 0 16 Sep 2018
Likelihood-free inference with emulator networks Jan-Matthis Lueckmann Giacomo Bassetto Theofanis Karaletsos Jakob H. Macke 22 124 0 23 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 60 358 0 18 May 2018
Approximating the Likelihood in Approximate Bayesian Computation Christopher C. Drovandi Clara Grazian Kerrie Mengersen Christian P. Robert 27 12 0 18 Mar 2018
ABC and Indirect Inference Christopher C. Drovandi 14 9 0 06 Mar 2018
Overview of Approximate Bayesian Computation Scott A. Sisson Y. Fan Mark Beaumont 16 45 0 27 Feb 2018
Bootstrapped synthetic likelihood R. Everitt 31 14 0 15 Nov 2017
Flexible statistical inference for mechanistic models of neural dynamics Jan-Matthis Lueckmann P. J. Gonçalves Giacomo Bassetto Kaan Öcal M. Nonnenmacher Jakob H. Macke 34 240 0 06 Nov 2017