MINIMALIST: Mutual INformatIon Maximization for Amortized Likelihood Inference from Sampled Trajectories

3 June 2021

Papers citing "MINIMALIST: Mutual INformatIon Maximization for Amortized Likelihood Inference from Sampled Trajectories"

24 / 24 papers shown

Title
Gradient-based Bayesian Experimental Design for Implicit Models using Mutual Information Lower Bounds Steven Kleinegesse Michael U. Gutmann FedML 59 25 0 10 May 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
Neural Approximate Sufficient Statistics for Implicit Models Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 394 84 0 20 Oct 2020
Array Programming with NumPy Charles R. Harris K. Millman S. Walt R. Gommers Pauli Virtanen ... Tyler Reddy Warren Weckesser Hameer Abbasi C. Gohlke T. Oliphant 154 14,959 0 18 Jun 2020
Sequential Bayesian Experimental Design for Implicit Models via Mutual Information Steven Kleinegesse Christopher C. Drovandi Michael U. Gutmann 111 28 0 20 Mar 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 176 851 0 04 Nov 2019
CCMI : Classifier based Conditional Mutual Information Estimation Sudipto Mukherjee Himanshu Asnani Sreeram Kannan VLM 110 81 0 05 Jun 2019
Automatic Posterior Transformation for Likelihood-Free Inference David S. Greenberg M. Nonnenmacher Jakob H. Macke 373 329 0 17 May 2019
On Variational Bounds of Mutual Information Ben Poole Sherjil Ozair Aaron van den Oord Alexander A. Alemi George Tucker SSL 104 807 0 16 May 2019
Variational Bayesian Optimal Experimental Design Adam Foster M. Jankowiak Eli Bingham Paul Horsfall Yee Whye Teh Tom Rainforth Noah D. Goodman 81 137 0 13 Mar 2019
Efficient Bayesian Experimental Design for Implicit Models Steven Kleinegesse Michael U. Gutmann 62 50 0 23 Oct 2018
Noise Contrastive Estimation and Negative Sampling for Conditional Models: Consistency and Statistical Efficiency Zhuang Ma Michael Collins 64 147 0 06 Sep 2018
Representation Learning with Contrastive Predictive Coding Aaron van den Oord Yazhe Li Oriol Vinyals DRL SSL 320 10,302 0 10 Jul 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 530 367 0 18 May 2018
Overview of Approximate Bayesian Computation Scott A. Sisson Y. Fan Mark Beaumont 54 46 0 27 Feb 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 171 245 0 06 Nov 2017
Likelihood-free inference by ratio estimation Owen Thomas Ritabrata Dutta J. Corander Samuel Kaski Michael U. Gutmann 190 151 0 30 Nov 2016
Edward: A library for probabilistic modeling, inference, and criticism Dustin Tran A. Kucukelbir Adji Bousso Dieng Maja R. Rudolph Dawen Liang David M. Blei 56 301 0 31 Oct 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 161 158 0 20 May 2016
Exploring the Limits of Language Modeling Rafal Jozefowicz Oriol Vinyals M. Schuster Noam M. Shazeer Yonghui Wu 191 1,145 0 07 Feb 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 313 4,182 0 21 May 2015
Estimating divergence functionals and the likelihood ratio by convex risk minimization X. Nguyen Martin J. Wainwright Michael I. Jordan 223 803 0 04 Sep 2008