Robust and integrative Bayesian neural networks for likelihood-free
parameter inference

Robust and integrative Bayesian neural networks for likelihood-free parameter inference

12 February 2021

Richard M. Jiang

Linda R. Petzold

Andreas Hellander

Papers citing "Robust and integrative Bayesian neural networks for likelihood-free parameter inference"

19 / 19 papers shown

Title
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 231 195 0 12 Jan 2021
Neural Approximate Sufficient Statistics for Implicit Models Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 312 84 0 20 Oct 2020
On Contrastive Learning for Likelihood-free Inference Conor Durkan Iain Murray George Papamakarios BDL 179 123 0 10 Feb 2020
Convolutional Neural Networks as Summary Statistics for Approximate Bayesian Computation Mattias Åkesson Prashant Singh Fredrik Wrede Andreas Hellander BDL 79 33 0 31 Jan 2020
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 148 846 0 04 Nov 2019
Bayesian epidemiological modeling over high-resolution network data Stefan Engblom Robin Eriksson S. Widgren 78 15 0 25 Oct 2019
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 153 773 0 10 Jun 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 292 329 0 17 May 2019
Partially Exchangeable Networks and Architectures for Learning Summary Statistics in Approximate Bayesian Computation Samuel Wiqvist Pierre-Alexandre Mattei Umberto Picchini J. Frellsen BDL 127 32 0 29 Jan 2019
Dynamic Likelihood-free Inference via Ratio Estimation (DIRE) Traiko Dinev Michael U. Gutmann 115 27 0 23 Oct 2018
Likelihood-free inference with emulator networks Jan-Matthis Lueckmann Giacomo Bassetto Theofanis Karaletsos Jakob H. Macke 138 128 0 23 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 420 366 0 18 May 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 139 245 0 06 Nov 2017
Masked Autoregressive Flow for Density Estimation George Papamakarios Theo Pavlakou Iain Murray 177 1,351 0 19 May 2017
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 138 158 0 20 May 2016
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network Bai Jiang Tung-Yu Wu Charles Yang Zheng W. Wong BDL 217 141 0 08 Oct 2015
Adapting the ABC distance function D. Prangle 78 94 0 03 Jul 2015
Scalable Inference for Markov Processes with Intractable Likelihoods J. Owen D. Wilkinson Colin S. Gillespie TPM 111 29 0 26 Mar 2014
Approximate Bayesian Computational methods Jean-Michel Marin Pierre Pudlo Christian P. Robert Robin J. Ryder 192 862 0 05 Jan 2011

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