Group equivariant neural posterior estimation

25 November 2021

Jakob H. Macke

Papers citing "Group equivariant neural posterior estimation"

22 / 22 papers shown

Title
Real-time gravitational-wave science with neural posterior estimation Maximilian Dax Stephen R. Green J. Gair Jakob H. Macke A. Buonanno Bernhard Schölkopf 55 134 0 23 Jun 2021
Benchmarking Simulation-Based Inference Jan-Matthis Lueckmann Jan Boelts David S. Greenberg P. J. Gonçalves Jakob H. Macke 169 192 0 12 Jan 2021
Lightning-Fast Gravitational Wave Parameter Inference through Neural Amortization Arnaud Delaunoy Antoine Wehenkel T. Hinderer S. Nissanke Christoph Weniger A. Williamson Gilles Louppe 11 30 0 24 Oct 2020
Neural Approximate Sufficient Statistics for Implicit Models Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 156 83 0 20 Oct 2020
Sampling using $SU(N)$ gauge equivariant flows D. Boyda G. Kanwar S. Racanière Danilo Jimenez Rezende M. S. Albergo Kyle Cranmer D. Hackett P. Shanahan 46 127 0 12 Aug 2020
Complete parameter inference for GW150914 using deep learning Stephen R. Green J. Gair BDL 54 89 0 07 Aug 2020
Normalizing Flows for Probabilistic Modeling and Inference George Papamakarios Eric T. Nalisnick Danilo Jimenez Rezende S. Mohamed Balaji Lakshminarayanan TPM AI4CE 120 1,662 0 05 Dec 2019
PyTorch: An Imperative Style, High-Performance Deep Learning Library Adam Paszke Sam Gross Francisco Massa Adam Lerer James Bradbury ... Sasank Chilamkurthy Benoit Steiner Lu Fang Junjie Bai Soumith Chintala ODL 126 42,038 0 03 Dec 2019
The frontier of simulation-based inference Kyle Cranmer Johann Brehmer Gilles Louppe AI4CE 94 834 0 04 Nov 2019
Learning Bayesian posteriors with neural networks for gravitational-wave inference A. J. Chua M. Vallisneri BDL UQCV 10 78 0 12 Sep 2019
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale A. G. Baydin Lei Shao W. Bhimji Lukas Heinrich Lawrence Meadows ... Philip Torr Victor W. Lee Kyle Cranmer P. Prabhat Frank Wood 51 55 0 08 Jul 2019
Neural Spline Flows Conor Durkan Artur Bekasov Iain Murray George Papamakarios DRL 98 761 0 10 Jun 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 141 319 0 17 May 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 45 20 0 10 Mar 2019
Mining gold from implicit models to improve likelihood-free inference Johann Brehmer Gilles Louppe J. Pavez Kyle Cranmer AI4CE TPM 92 181 0 30 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 218 360 0 18 May 2018
Revisiting Classifier Two-Sample Tests David Lopez-Paz Maxime Oquab 95 397 0 20 Oct 2016
Group Equivariant Convolutional Networks Taco S. Cohen Max Welling BDL 106 1,917 0 24 Feb 2016
Learning Summary Statistic for Approximate Bayesian Computation via Deep Neural Network Bai Jiang Tung-Yu Wu Charles Yang Zheng W. Wong BDL 81 140 0 08 Oct 2015
Spatial Transformer Networks Max Jaderberg Karen Simonyan Andrew Zisserman Koray Kavukcuoglu 249 7,361 0 05 Jun 2015
Variational Inference with Normalizing Flows Danilo Jimenez Rezende S. Mohamed DRL BDL 234 4,143 0 21 May 2015
Bayesian Optimization for Likelihood-Free Inference of Simulator-Based Statistical Models Michael U. Gutmann J. Corander 92 285 0 14 Jan 2015