A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful

13 October 2021

Papers citing "A Trust Crisis In Simulation-Based Inference? Your Posterior Approximations Can Be Unfaithful"

37 / 37 papers shown

Title
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 235 2 0 17 Jan 2025
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 185 0 0 22 Jul 2024
Bayesian Synthetic Likelihood David T. Frazier Christopher C. Drovandi David J. Nott 168 220 0 09 May 2023
Robust Bayesian Inference for Simulator-based Models via the MMD Posterior Bootstrap Charita Dellaporta Jeremias Knoblauch Theodoros Damoulas F. Briol 71 43 0 09 Feb 2022
Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference François Rozet Gilles Louppe 90 6 0 01 Oct 2021
Robust Generalised Bayesian Inference for Intractable Likelihoods Takuo Matsubara Jeremias Knoblauch François‐Xavier Briol Chris J. Oates UQCV 51 79 0 15 Apr 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 259 195 0 12 Jan 2021
Score Matched Neural Exponential Families for Likelihood-Free Inference Lorenzo Pacchiardi Ritabrata Dutta 165 27 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 69 29 0 30 Nov 2020
Generalized Posteriors in Approximate Bayesian Computation Sebastian M. Schmon Patrick W Cannon Jeremias Knoblauch 69 25 0 17 Nov 2020
Distortion estimates for approximate Bayesian inference Hanwen Xing Geoff K. Nicholls J. Lee 33 7 0 19 Jun 2020
Confidence Sets and Hypothesis Testing in a Likelihood-Free Inference Setting Niccolò Dalmasso Rafael Izbicki Ann B. Lee 51 21 0 24 Feb 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 204 123 0 10 Feb 2020
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 174 851 0 04 Nov 2019
Convergence diagnostics for Markov chain Monte Carlo Vivekananda Roy 64 219 0 26 Sep 2019
Mining for Dark Matter Substructure: Inferring subhalo population properties from strong lenses with machine learning Johann Brehmer S. Mishra-Sharma Joeri Hermans Gilles Louppe Kyle Cranmer 68 74 0 04 Sep 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 368 329 0 17 May 2019
Bayesian inference using synthetic likelihood: asymptotics and adjustments David T. Frazier David J. Nott Christopher C. Drovandi Robert Kohn 47 41 0 13 Feb 2019
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 527 367 0 18 May 2018
A Guide to Constraining Effective Field Theories with Machine Learning Johann Brehmer Kyle Cranmer Gilles Louppe J. Pavez 212 141 0 30 Apr 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 166 245 0 06 Nov 2017
Data analysis recipes: Using Markov Chain Monte Carlo D. Hogg D. Foreman-Mackey 63 210 0 17 Oct 2017
Self-Normalizing Neural Networks Günter Klambauer Thomas Unterthiner Andreas Mayr Sepp Hochreiter 454 2,511 0 08 Jun 2017
Simple and Scalable Predictive Uncertainty Estimation using Deep Ensembles Balaji Lakshminarayanan Alexander Pritzel Charles Blundell UQCV BDL 831 5,811 0 05 Dec 2016
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 185 151 0 30 Nov 2016
Revisiting Classifier Two-Sample Tests David Lopez-Paz Maxime Oquab 155 402 0 20 Oct 2016
Faster Eigenvector Computation via Shift-and-Invert Preconditioning Dan Garber Laurent Dinh Chi Jin Jascha Narain Sohl-Dickstein Samy Bengio Praneeth Netrapalli Aaron Sidford 263 3,696 0 26 May 2016
Approximating Likelihood Ratios with Calibrated Discriminative Classifiers Kyle Cranmer J. Pavez Gilles Louppe 127 227 0 06 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 310 4,179 0 21 May 2015
Training generative neural networks via Maximum Mean Discrepancy optimization Gintare Karolina Dziugaite Daniel M. Roy Zoubin Ghahramani GAN 84 530 0 14 May 2015
Adam: A Method for Stochastic Optimization Diederik P. Kingma Jimmy Ba ODL 1.8K 150,039 0 22 Dec 2014
NICE: Non-linear Independent Components Estimation Laurent Dinh David M. Krueger Yoshua Bengio DRL BDL 121 2,258 0 30 Oct 2014
Bounding the Test Log-Likelihood of Generative Models Yoshua Bengio L. Yao Kyunghyun Cho TPM 71 23 0 24 Nov 2013
Diagnostic tools of approximate Bayesian computation using the coverage property D. Prangle M. Blum Gordana C. Popovic Scott A. Sisson 94 68 0 14 Jan 2013
Simulation-based model selection for dynamical systems in systems and population biology Tina Toni M. Stumpf 122 290 0 09 Nov 2009
Non-linear regression models for Approximate Bayesian Computation M. Blum O. François 215 484 0 24 Sep 2008
Adaptive approximate Bayesian computation Mark Beaumont J. Cornuet Jean-Michel Marin Christian P. Robert 183 644 0 15 May 2008