Hamiltonian ABC

6 March 2015

Papers citing "Hamiltonian ABC"

21 / 21 papers shown

Title
Approximate Bayesian Computation for an Explicit-Duration Hidden Markov Model of COVID-19 Hospital TrajectoriesMachine Learning in Health Care (MLHC), 2021 Gian Marco Visani A. Lee C. Nguyen David M Kent J. Wong Joshua T. Cohen M. C. Hughes OOD 149 1 0 28 Apr 2021
Neural Approximate Sufficient Statistics for Implicit ModelsInternational Conference on Learning Representations (ICLR), 2020 Yanzhi Chen Dinghuai Zhang Michael U. Gutmann Aaron Courville Zhanxing Zhu 546 95 0 20 Oct 2020
Langevin Monte Carlo: random coordinate descent and variance reductionJournal of machine learning research (JMLR), 2020 Zhiyan Ding Qin Li BDL 578 13 0 26 Jul 2020
Variance reduction for Random Coordinate Descent-Langevin Monte Carlo Zhiyan Ding Qin Li BDL 281 0 0 10 Jun 2020
Neural Density Estimation and Likelihood-free Inference George Papamakarios BDL DRL 195 51 0 29 Oct 2019
Privacy-preserving Federated Bayesian Learning of a Generative Model for Imbalanced Classification of Clinical Data S. Hahn Junghye Lee FedML 189 5 0 18 Oct 2019
BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic LikelihoodJournal of Statistical Software (JSS), 2019 Ziwen An Leah F. South Christopher C. Drovandi 163 14 0 25 Jul 2019
Likelihood-free MCMC with Amortized Approximate Ratio Estimators Joeri Hermans Volodimir Begy Gilles Louppe 386 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 462 195 0 30 May 2018
Sequential Neural Likelihood: Fast Likelihood-free Inference with Autoregressive Flows George Papamakarios D. Sterratt Iain Murray BDL 798 415 0 18 May 2018
ABC Samplers Y. Fan Scott A. Sisson 161 30 0 26 Feb 2018
Easy High-Dimensional Likelihood-Free Inference Vinay Jethava Devdatt Dubhashi BDL GAN 510 3 0 29 Nov 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 306 287 0 06 Nov 2017
Adversarial Variational Optimization of Non-Differentiable Simulators Gilles Louppe Joeri Hermans Kyle Cranmer GAN 398 69 0 22 Jul 2017
Pseudo-Marginal Hamiltonian Monte CarloJournal of machine learning research (JMLR), 2016 Johan Alenlöv Arnaud Doucet Fredrik Lindsten 196 23 0 08 Jul 2016
Automatic Variational ABC Alexander Moreno T. Adel Edward Meeds James M. Rehg Max Welling 280 12 0 28 Jun 2016
Asymptotically exact inference in differentiable generative models Matthew M. Graham Amos J. Storkey BDL 413 35 0 25 May 2016
Fast $ε$ -free Inference of Simulation Models with Bayesian Conditional Density Estimation George Papamakarios Iain Murray TPM 355 165 0 20 May 2016
A Markov Jump Process for More Efficient Hamiltonian Monte Carlo A. Berger M. Mudigonda M. DeWeese Jascha Narain Sohl-Dickstein 233 1 0 13 Sep 2015
Optimization Monte Carlo: Efficient and Embarrassingly Parallel Likelihood-Free InferenceNeural Information Processing Systems (NeurIPS), 2015 Edward Meeds Max Welling 263 35 0 11 Jun 2015
Gradient-free Hamiltonian Monte Carlo with Efficient Kernel Exponential FamiliesNeural Information Processing Systems (NeurIPS), 2015 Heiko Strathmann Dino Sejdinovic Samuel Livingstone Z. Szabó Arthur Gretton BDL 173 76 0 08 Jun 2015