Sequential Monte Carlo with Adaptive Weights for Approximate Bayesian Computation

26 March 2015

Papers citing "Sequential Monte Carlo with Adaptive Weights for Approximate Bayesian Computation"

33 / 33 papers shown

Title
Multilevel neural simulation-based inference Yuga Hikida Ayush Bharti Niall Jeffrey F. Briol 72 0 0 06 Jun 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 283 2 0 17 Jan 2025
Stratified distance space improves the efficiency of sequential samplers for approximate Bayesian computation Henri Pesonen J. Corander 69 0 0 30 Dec 2023
Optimal simulation-based Bayesian decisions Justin Alsing Thomas D. P. Edwards Benjamin Dan Wandelt 65 1 0 09 Nov 2023
Reliable Gradient-free and Likelihood-free Prompt Tuning Maohao Shen S. Ghosh P. Sattigeri Subhro Das Yuheng Bu G. Wornell VLM 115 12 0 30 Apr 2023
Towards black-box parameter estimation Amanda Lenzi Haavard Rue 404 5 0 27 Mar 2023
Sequential Neural Score Estimation: Likelihood-Free Inference with Conditional Score Based Diffusion Models Louis Sharrock J. Simons Song Liu Mark Beaumont DiffM 126 39 0 10 Oct 2022
Guided sequential ABC schemes for intractable Bayesian models Umberto Picchini M. Tamborrino 152 8 0 24 Jun 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 74 14 0 18 Mar 2022
Weakly informative priors and prior-data conflict checking for likelihood-free inference Atlanta Chakraborty David J. Nott Michael Evans 65 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 88 45 0 09 Feb 2022
Measuring the accuracy of likelihood-free inference Aden Forrow R. Baker 47 2 0 15 Dec 2021
Composite Goodness-of-fit Tests with Kernels Oscar Key Arthur Gretton F. Briol T. Fernandez 126 16 0 19 Nov 2021
Validation and Inference of Agent Based Models D. Townsend AI4CE 54 2 0 08 Jul 2021
A Comparison of Likelihood-Free Methods With and Without Summary Statistics Christopher C. Drovandi David T. Frazier 82 35 0 03 Mar 2021
Perspectives on Constrained Forecasting M. West 90 8 0 21 Jul 2020
Increasing the efficiency of Sequential Monte Carlo samplers through the use of approximately optimal L-kernels P. L. Green Robert E. Moore Ryan J Jackson Jinglai Li Simon Maskell 74 13 0 24 Apr 2020
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 102 47 0 29 Oct 2019
Minimax Confidence Intervals for the Sliced Wasserstein Distance Tudor Manole Sivaraman Balakrishnan Larry A. Wasserman 177 36 0 17 Sep 2019
Adaptive Approximate Bayesian Computation Tolerance Selection U. Simola J. Cisewski-Kehe Michael U. Gutmann J. Corander 61 24 0 21 Jun 2019
BayesSim: adaptive domain randomization via probabilistic inference for robotics simulators F. Ramos Rafael Possas Dieter Fox 62 158 0 04 Jun 2019
Optimal proposals for Approximate Bayesian Computation Justin Alsing Benjamin Dan Wandelt S. Feeney 133 6 0 18 Aug 2018
Variational Implicit Processes Chao Ma Yingzhen Li José Miguel Hernández-Lobato BDL 121 70 0 06 Jun 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 552 370 0 18 May 2018
ABC Samplers Y. Fan Scott A. Sisson 63 29 0 26 Feb 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 201 249 0 06 Nov 2017
An effective likelihood-free approximate computing method with statistical inferential guarantees S. Thornton Wentao Li Min‐ge Xie 46 2 0 29 May 2017
On parameter estimation with the Wasserstein distance Espen Bernton H. Shakespeare Mathieu Gerber Christian P. Robert 117 78 0 18 Jan 2017
Convergence of Regression Adjusted Approximate Bayesian Computation Wentao Li Paul Fearnhead 166 36 0 22 Sep 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 200 158 0 20 May 2016
Adapting the ABC distance function D. Prangle 112 95 0 03 Jul 2015
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference Edward Meeds Max Welling 185 36 0 11 Jun 2015
Approximate Bayesian Computation for Forward Modeling in Cosmology Joel Akeret Alexandre Réfrégier A. Amara Sebastian Seehars C. Hasner 75 90 0 27 Apr 2015