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Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference

31 January 2023

Christopher C. Drovandi

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Papers citing "Misspecification-robust Sequential Neural Likelihood for Simulation-based Inference"

38 / 38 papers shown

Title
Learning Robust Statistics for Simulation-based Inference under Model Misspecification Daolang Huang Ayush Bharti Amauri Souza Luigi Acerbi Samuel Kaski 93 35 0 25 May 2023
Bayesian Synthetic Likelihood David T. Frazier Christopher C. Drovandi David J. Nott 177 220 0 09 May 2023
Bayesian score calibration for approximate models Joshua J. Bon D. Warne David J. Nott Christopher C. Drovandi 54 3 0 10 Nov 2022
Investigating the Impact of Model Misspecification in Neural Simulation-based Inference Patrick W Cannon Daniel Ward Sebastian M. Schmon 76 36 0 05 Sep 2022
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap Charita Dellaporta Jeremias Knoblauch Theodoros Damoulas F. Briol 74 45 0 09 Feb 2022
Learning Summary Statistics for Bayesian Inference with Autoencoders Carlo Albert S. Ulzega Firat Ozdemir Fernando Perez-Cruz Antonietta Mira BDL 74 13 0 28 Jan 2022
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 51 16 0 26 Oct 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 60 79 0 15 Apr 2021
Sequential Neural Posterior and Likelihood Approximation Samuel Wiqvist J. Frellsen Umberto Picchini BDL 415 33 0 12 Feb 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 259 198 0 12 Jan 2021
Score Matched Neural Exponential Families for Likelihood-Free Inference Lorenzo Pacchiardi Ritabrata Dutta 171 28 0 20 Dec 2020
Towards constraining warm dark matter with stellar streams through neural simulation-based inference Joeri Hermans N. Banik Christoph Weniger G. Bertone Gilles Louppe 76 29 0 30 Nov 2020
Generalized Posteriors in Approximate Bayesian Computation Sebastian M. Schmon Patrick W Cannon Jeremias Knoblauch 88 25 0 17 Nov 2020
Sharpness-Aware Minimization for Efficiently Improving Generalization Pierre Foret Ariel Kleiner H. Mobahi Behnam Neyshabur AAML 199 1,358 0 03 Oct 2020
Robust Approximate Bayesian Computation: An Adjustment Approach David T. Frazier Christopher C. Drovandi Rubén Loaiza-Maya 45 13 0 07 Aug 2020
BayesFlow: Learning complex stochastic models with invertible neural networks Stefan T. Radev U. Mertens A. Voss Lynton Ardizzone Ullrich Kothe BDL 290 197 0 13 Mar 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 211 124 0 10 Feb 2020
Composable Effects for Flexible and Accelerated Probabilistic Programming in NumPyro Du Phan Neeraj Pradhan M. Jankowiak 61 360 0 24 Dec 2019
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 209 1,713 0 05 Dec 2019
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 190 854 0 04 Nov 2019
MMD-Bayes: Robust Bayesian Estimation via Maximum Mean Discrepancy Badr-Eddine Chérief-Abdellatif Pierre Alquier 161 75 0 29 Sep 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 387 331 0 17 May 2019
Robust Approximate Bayesian Inference with Synthetic Likelihood David T. Frazier Christopher C. Drovandi 48 45 0 09 Apr 2019
$Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC$ Rank-normalization, folding, and localization: An improved $\widehat{R}$ for assessing convergence of MCMC Aki Vehtari Andrew Gelman Daniel P. Simpson Bob Carpenter Paul-Christian Bürkner 52 940 0 19 Mar 2019
Pyro: Deep Universal Probabilistic Programming Eli Bingham Jonathan P. Chen M. Jankowiak F. Obermeyer Neeraj Pradhan Theofanis Karaletsos Rohit Singh Paul A. Szerlip Paul Horsfall Noah D. Goodman BDL GP 158 1,057 0 18 Oct 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 533 370 0 18 May 2018
ELFI: Engine for Likelihood-Free Inference Jarno Lintusaari H. Vuollekoski A. Kangasrääsiö Kusti Skytén Marko Jarvenpaa Pekka Marttinen Michael U. Gutmann Aki Vehtari J. Corander Samuel Kaski 55 73 0 02 Aug 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 215 1,360 0 19 May 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 842 5,841 0 05 Dec 2016
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 190 151 0 30 Nov 2016
Revisiting Classifier Two-Sample Tests David Lopez-Paz Maxime Oquab 163 405 0 20 Oct 2016
A Baseline for Detecting Misclassified and Out-of-Distribution Examples in Neural Networks Dan Hendrycks Kevin Gimpel UQCV 168 3,472 0 07 Oct 2016
Automatic differentiation in machine learning: a survey A. G. Baydin Barak A. Pearlmutter Alexey Radul J. Siskind PINN AI4CE ODL 168 2,816 0 20 Feb 2015
The Rate of Convergence for Approximate Bayesian Computation Stuart Barber J. Voss M. Webster 63 80 0 08 Nov 2013
A General Framework for Updating Belief Distributions Pier Giovanni Bissiri Chris Holmes S. Walker 225 479 0 27 Jun 2013
The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo Matthew D. Hoffman Andrew Gelman 169 4,309 0 18 Nov 2011
Relevant statistics for Bayesian model choice Jean-Michel Marin N. Pillai Christian P. Robert Judith Rousseau 83 144 0 21 Oct 2011
The pseudo-marginal approach for efficient Monte Carlo computations Christophe Andrieu Gareth O. Roberts 184 895 0 31 Mar 2009