Automatic Posterior Transformation for Likelihood-Free Inference

17 May 2019

Jakob H. Macke

Papers citing "Automatic Posterior Transformation for Likelihood-Free Inference"

36 / 36 papers shown

Title
Multifidelity Simulation-based Inference for Computationally Expensive Simulators Anastasia N. Krouglova Hayden R. Johnson Basile Confavreux Michael Deistler P. J. Gonçalves 214 3 0 17 Feb 2025
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation Yifei Xiong Xiliang Yang Sanguo Zhang Zhijian He 240 2 0 17 Jan 2025
TRADE: Transfer of Distributions between External Conditions with Normalizing Flows Stefan Wahl Armand Rousselot Felix Dräxler Ullrich Kothe Ullrich Köthe 160 0 0 25 Oct 2024
Inverse decision-making using neural amortized Bayesian actors Dominik Straub Tobias F. Niehues Jan Peters Constantin Rothkopf 172 1 0 04 Sep 2024
Amortized Bayesian Multilevel Models Daniel Habermann Marvin Schmitt Lars Kühmichel Andreas Bulling Stefan T. Radev Paul-Christian Bürkner 206 4 0 23 Aug 2024
SoftCVI: Contrastive variational inference with self-generated soft labels Daniel Ward Mark Beaumont Matteo Fasiolo BDL 199 0 0 22 Jul 2024
Neural Bayes Estimators for Irregular Spatial Data using Graph Neural Networks Matthew Sainsbury-Dale A. Zammit‐Mangion J. Richards Raphael Huser 633 15 0 04 Oct 2023
Recurrent machines for likelihood-free inference Arthur Pesah Antoine Wehenkel Gilles Louppe 117 5 0 30 Nov 2018
Sequential Neural Methods for Likelihood-free Inference Conor Durkan George Papamakarios Iain Murray BDL 169 25 0 21 Nov 2018
Dynamic Likelihood-free Inference via Ratio Estimation (DIRE) Traiko Dinev Michael U. Gutmann 141 27 0 23 Oct 2018
Glow: Generative Flow with Invertible 1x1 Convolutions Diederik P. Kingma Prafulla Dhariwal BDL DRL 295 3,134 0 09 Jul 2018
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 157 181 0 30 May 2018
Likelihood-free inference with emulator networks Jan-Matthis Lueckmann Giacomo Bassetto Theofanis Karaletsos Jakob H. Macke 163 128 0 23 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 533 367 0 18 May 2018
A Likelihood-Free Inference Framework for Population Genetic Data using Exchangeable Neural Networks Jeffrey Chan Valerio Perrone J. Spence Paul A. Jenkins Sara Mathieson Yun S. Song 317 107 0 16 Feb 2018
Variational Inference over Non-differentiable Cardiac Simulators using Bayesian Optimization Adam McCarthy Blanca Rodriguez A. Mincholé 154 5 0 09 Dec 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 174 245 0 06 Nov 2017
Adversarial Variational Optimization of Non-Differentiable Simulators Gilles Louppe Joeri Hermans Kyle Cranmer GAN 153 66 0 22 Jul 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 210 1,354 0 19 May 2017
Efficient acquisition rules for model-based approximate Bayesian computation Marko Jarvenpaa Michael U. Gutmann Arijus Pleska Aki Vehtari Pekka Marttinen TPM 160 69 0 03 Apr 2017
Deep Sets Manzil Zaheer Satwik Kottur Siamak Ravanbakhsh Barnabás Póczós Ruslan Salakhutdinov Alex Smola 408 2,464 0 10 Mar 2017
Using Synthetic Data to Train Neural Networks is Model-Based Reasoning T. Le A. G. Baydin R. Zinkov Frank Wood SyDa OOD 148 88 0 02 Mar 2017
Variational Inference using Implicit Distributions Ferenc Huszár DRL GAN 160 135 0 27 Feb 2017
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 190 151 0 30 Nov 2016
Learning in Implicit Generative Models S. Mohamed Balaji Lakshminarayanan GAN 190 416 0 11 Oct 2016
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network Bai Jiang Tung-Yu Wu Charles Yang Zheng W. Wong BDL 305 142 0 08 Oct 2015
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 318 4,182 0 21 May 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models Michael U. Gutmann J. Corander 157 287 0 14 Jan 2015
Likelihood free inference for Markov processes: a comparison J. Owen D. Wilkinson Colin S. Gillespie 199 33 0 02 Oct 2014
Likelihood-free inference via classification Michael U. Gutmann Ritabrata Dutta Samuel Kaski J. Corander 174 63 0 18 Jul 2014
Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation Kyunghyun Cho B. V. Merrienboer Çağlar Gülçehre Dzmitry Bahdanau Fethi Bougares Holger Schwenk Yoshua Bengio AIMat 1.0K 23,354 0 03 Jun 2014
Approximate Bayesian Computation via Regression Density Estimation Yanan Fan David J. Nott Scott A. Sisson 165 62 0 06 Dec 2012
A Comparative Review of Dimension Reduction Methods in Approximate Bayesian Computation M. Blum M. Nunes D. Prangle Scott A. Sisson 183 364 0 16 Feb 2012
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 185 644 0 15 May 2008