Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models

14 January 2015

Papers citing "Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models"

50 / 51 papers shown

Title
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
Bayesian Adaptive Calibration and Optimal Design Rafael Oliveira Dino Sejdinovic David Howard Edwin Bonilla 113 0 0 20 Jan 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
Compositional simulation-based inference for time series Manuel Gloeckler S. Toyota Kenji Fukumizu Jakob H Macke 45 1 0 05 Nov 2024
Full-waveform earthquake source inversion using simulation-based inference A. A. Saoulis Davide Piras A. Spurio Mancini B. Joachimi A. M. G. Ferreira 40 0 0 30 Oct 2024
Global Optimisation of Black-Box Functions with Generative Models in the Wasserstein Space Tigran Ramazyan M. Hushchyn D. Derkach 36 0 0 16 Jul 2024
Copula Approximate Bayesian Computation Using Distribution Random Forests G. Karabatsos 42 1 0 28 Feb 2024
Leveraging Nested MLMC for Sequential Neural Posterior Estimation with Intractable Likelihoods Xiliang Yang Yifei Xiong Zhijian He 36 0 0 30 Jan 2024
Optimal simulation-based Bayesian decisions Justin Alsing Thomas D. P. Edwards Benjamin Dan Wandelt 33 1 0 09 Nov 2023
Learning Hybrid Dynamics Models With Simulator-Informed Latent States K. Ensinger Sebastian Ziesche Sebastian Trimpe 37 1 0 06 Sep 2023
Bayesian Synthetic Likelihood David T. Frazier Christopher C. Drovandi David J. Nott 39 217 0 09 May 2023
A Bayesian Optimization approach for calibrating large-scale activity-based transport models S. Agriesti Vladimir Kuzmanovski Jaakko Hollmén C. Roncoli Bat-hen Nahmias-Biran 29 5 0 07 Feb 2023
Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference Ayush Bharti Masha Naslidnyk Oscar Key Samuel Kaski F. Briol 40 12 0 27 Jan 2023
Data-driven Science and Machine Learning Methods in Laser-Plasma Physics Andreas Döpp C. Eberle S. Howard F. Irshad Jinpu Lin M. Streeter AI4CE 32 63 0 30 Nov 2022
Differentiable User Models Alex Hamalainen Mustafa Mert cCelikok Samuel Kaski 26 1 0 29 Nov 2022
Simulation-based inference of Bayesian hierarchical models while checking for model misspecification F. Leclercq 33 6 0 22 Sep 2022
Bayesian Optimization with Informative Covariance Afonso Eduardo Michael U. Gutmann 24 3 0 04 Aug 2022
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination Masaki Adachi Satoshi Hayakawa Martin Jørgensen Harald Oberhauser Michael A. Osborne 22 20 0 09 Jun 2022
Nonparametric likelihood-free inference with Jensen-Shannon divergence for simulator-based models with categorical output J. Corander Ulpu Remes Ida Holopainen T. Koski 25 0 0 22 May 2022
Optimality in Noisy Importance Sampling F. Llorente Luca Martino Jesse Read D. Delgado 41 5 0 07 Jan 2022
Approximating Bayes in the 21st Century G. Martin David T. Frazier Christian P. Robert 41 26 0 20 Dec 2021
Group equivariant neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Michael Deistler Bernhard Schölkopf Jakob H. Macke BDL 33 31 0 25 Nov 2021
Likelihood-Free Inference in State-Space Models with Unknown Dynamics Alexander Aushev Thong Tran Henri Pesonen Andrew Howes Samuel Kaski 28 1 0 02 Nov 2021
Truncated Marginal Neural Ratio Estimation Benjamin Kurt Miller A. Cole Patrick Forré Gilles Louppe Christoph Weniger 39 37 0 02 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
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 34 33 0 12 Feb 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 104 185 0 12 Jan 2021
Neural Approximate Sufficient Statistics for Implicit Models Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 30 79 0 20 Oct 2020
Generalised Bayes Updates with $f$ -divergences through Probabilistic Classifiers Owen Thomas Henri Pesonen J. Corander FedML 29 2 0 08 Jul 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
Bayesian Experimental Design for Implicit Models by Mutual Information Neural Estimation Steven Kleinegesse Michael U. Gutmann 26 66 0 19 Feb 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 45 117 0 10 Feb 2020
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
Likelihood-free approximate Gibbs sampling G. S. Rodrigues David J. Nott Scott A. Sisson 30 24 0 11 Jun 2019
Robust Optimisation Monte Carlo Borislav Ikonomov Michael U. Gutmann 14 8 0 01 Apr 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 32 20 0 10 Mar 2019
Adaptive Gaussian Copula ABC Yanzhi Chen Michael U. Gutmann TPM 18 27 0 27 Feb 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
Prepaid parameter estimation without likelihoods M. Mestdagh S. Verdonck Kristof Meers Tim Loossens F. Tuerlinckx 11 16 0 24 Dec 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 60 358 0 18 May 2018
Kernel Recursive ABC: Point Estimation with Intractable Likelihood T. Kajihara Motonobu Kanagawa Keisuke Yamazaki Kenji Fukumizu 37 13 0 23 Feb 2018
ABCpy: A High-Performance Computing Perspective to Approximate Bayesian Computation Ritabrata Dutta Marcel Schoengens Lorenzo Pacchiardi Avinash Ummadisingu Nicole Widmer Pierre Künzli J. Onnela Antonietta Mira 29 25 0 13 Nov 2017
Inverse Reinforcement Learning from Summary Data A. Kangasrääsiö Samuel Kaski OffRL 26 15 0 28 Mar 2017
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 42 145 0 30 Nov 2016
Learning in Implicit Generative Models S. Mohamed Balaji Lakshminarayanan GAN 25 412 0 11 Oct 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 32 158 0 20 May 2016
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free Inference Edward Meeds Max Welling 27 36 0 11 Jun 2015