MCMC using Hamiltonian dynamics

9 June 2012

Papers citing "MCMC using Hamiltonian dynamics"

50 / 1,031 papers shown

Title
Bayesian inverse problems with $l_1$ priors: a Randomize-then-Optimize approach Zheng Wang Johnathan M. Bardsley A. Solonen Tiangang Cui Youssef M. Marzouk 13 36 0 07 Jul 2016
Alternating Back-Propagation for Generator Network Tian Han Yang Lu Song-Chun Zhu Ying Nian Wu 6 4 0 28 Jun 2016
Approximate Marginal Posterior for Log Gaussian Cox Processes Shinichiro Shirota A. Gelfand 10 2 0 26 Jun 2016
Geometric MCMC for Infinite-Dimensional Inverse Problems A. Beskos Mark Girolami Shiwei Lan P. Farrell Andrew M. Stuart 13 137 0 20 Jun 2016
An Empirical Comparison of Sampling Quality Metrics: A Case Study for Bayesian Nonnegative Matrix Factorization A. Masood Weiwei Pan Finale Doshi-Velez 31 4 0 20 Jun 2016
Bayesian Inference on Matrix Manifolds for Linear Dimensionality Reduction Andrew J Holbrook A. Vandenberg-Rodes B. Shahbaba 19 15 0 14 Jun 2016
Reducing the error of Monte Carlo Algorithms by Learning Control Variates Brendan D. Tracey David Wolpert BDL 14 9 0 07 Jun 2016
A Dirichlet Form approach to MCMC Optimal Scaling Giacomo Zanella W. Kendall M. Bédard 18 9 0 05 Jun 2016
Fast Bayesian whole-brain fMRI analysis with spatial 3D priors Per Sidén Anders Eklund David Bolin M. Villani 12 47 0 03 Jun 2016
Synthesizing Dynamic Patterns by Spatial-Temporal Generative ConvNet Jianwen Xie Song-Chun Zhu Ying Nian Wu GAN 21 10 0 03 Jun 2016
CaMKII activation supports reward-based neural network optimization through Hamiltonian sampling Zhaofei Yu David Kappel R. Legenstein Sen Song Feng Chen Wolfgang Maass 16 1 0 01 Jun 2016
Quantifying the accuracy of approximate diffusions and Markov chains Jonathan H. Huggins James Y. Zou 39 29 0 20 May 2016
On Asymptotic Inference in Stochastic Differential Equations with Time-Varying Covariates Trisha Maitra S. Bhattacharya 9 3 0 11 May 2016
Likelihood Inflating Sampling Algorithm R. Entezari Radu V. Craiu Jeffrey S. Rosenthal 37 22 0 06 May 2016
Bayesian inference in hierarchical models by combining independent posteriors Ritabrata Dutta P. Blomstedt Samuel Kaski TPM 6 2 0 30 Mar 2016
The block-Poisson estimator for optimally tuned exact subsampling MCMC M. Quiroz Minh-Ngoc Tran M. Villani Robert Kohn Khue-Dung Dang 20 25 0 27 Mar 2016
Partition Functions from Rao-Blackwellized Tempered Sampling David Carlson Patrick Stinson Ari Pakman Liam Paninski 20 13 0 07 Mar 2016
Towards Unifying Hamiltonian Monte Carlo and Slice Sampling Yizhe Zhang Xiangyu Wang Changyou Chen Ricardo Henao Kai Fan Lawrence Carin 17 21 0 25 Feb 2016
Parsimonious modeling with Information Filtering Networks W. Barfuss Guido Previde Massara T. Di Matteo T. Aste 11 76 0 23 Feb 2016
Patterns of Scalable Bayesian Inference E. Angelino Matthew J. Johnson Ryan P. Adams 14 87 0 16 Feb 2016
An introduction to sampling via measure transport Youssef Marzouk Tarek A. El-Moselhy M. Parno Alessio Spantini OT 30 88 0 16 Feb 2016
A randomized maximum a posterior method for posterior sampling of high dimensional nonlinear Bayesian inverse problems Kainan Wang T. Bui-Thanh Omar Ghattas 11 46 0 11 Feb 2016
Variational Hamiltonian Monte Carlo via Score Matching Cheng Zhang B. Shahbaba Hongkai Zhao BDL 13 26 0 06 Feb 2016
Exchangeable Random Measures for Sparse and Modular Graphs with Overlapping Communities A. Todeschini Xenia Miscouridou François Caron 16 40 0 05 Feb 2016
On the Geometric Ergodicity of Hamiltonian Monte Carlo Samuel Livingstone M. Betancourt Simon Byrne Mark Girolami 26 116 0 29 Jan 2016
Fitting Bayesian item response models in Stata and Stan Robert Grant Daniel Furr Bob Carpenter Andrew Gelman 51 17 0 13 Jan 2016
Identifying the Optimal Integration Time in Hamiltonian Monte Carlo M. Betancourt 6 37 0 02 Jan 2016
The Reduced-Order Hybrid Monte Carlo Sampling Smoother A. Attia R. Stefanescu Adrian Sandu 12 30 0 02 Jan 2016
High-Order Stochastic Gradient Thermostats for Bayesian Learning of Deep Models Chunyuan Li Changyou Chen Kai Fan Lawrence Carin BDL 24 25 0 23 Dec 2015
A General Framework for Constrained Bayesian Optimization using Information-based Search José Miguel Hernández-Lobato M. Gelbart Ryan P. Adams Matthew W. Hoffman Zoubin Ghahramani 19 162 0 30 Nov 2015
Recycling intermediate steps to improve Hamiltonian Monte Carlo A. Nishimura David B. Dunson 20 9 0 21 Nov 2015
Model-based Dashboards for Customer Analytics Ryan Dew Asim Ansari 17 1 0 17 Nov 2015
Sequential estimation of intrinsic activity and synaptic input in single neurons by particle filtering with optimal importance density Pau Closas A. Guillamón 14 7 0 12 Nov 2015
Covariance-Controlled Adaptive Langevin Thermostat for Large-Scale Bayesian Sampling Xiaocheng Shang Zhanxing Zhu B. Leimkuhler Amos J. Storkey 22 51 0 29 Oct 2015
Scalable MCMC for Mixed Membership Stochastic Blockmodels Wenzhe Li Sungjin Ahn Max Welling BDL 32 42 0 16 Oct 2015
Distilling Model Knowledge George Papamakarios BDL 16 17 0 08 Oct 2015
Learning FRAME Models Using CNN Filters Yang Lu Song-Chun Zhu Ying Nian Wu GAN 17 66 0 28 Sep 2015
A Markov Jump Process for More Efficient Hamiltonian Monte Carlo A. Berger M. Mudigonda M. DeWeese Jascha Narain Sohl-Dickstein 27 1 0 13 Sep 2015
Gradient Scan Gibbs Sampler: an efficient algorithm for high-dimensional Gaussian distributions O. Féron F. Orieux J. Giovannelli 14 15 0 11 Sep 2015
Properties of the Affine Invariant Ensemble Sampler in high dimensions D. Huijser J. Goodman B. Brewer 17 23 0 07 Sep 2015
Bayesian Dropout Tue Herlau Morten Mørup Mikkel N. Schmidt BDL 22 2 0 12 Aug 2015
Adaptive Multiple Importance Sampling for Gaussian Processes Xiaoyu Xiong Václav Smídl Maurizio Filippone 27 6 0 05 Aug 2015
Orthogonal parallel MCMC methods for sampling and optimization Luca Martino Victor Elvira D. Luengo J. Corander F. Louzada 29 74 0 30 Jul 2015
A multiscale strategy for Bayesian inference using transport maps M. Parno Tarek A. El-Moselhy Youssef Marzouk 24 30 0 24 Jul 2015
Hessian corrections to the Metropolis Adjusted Langevin Algorithm T. House 19 2 0 22 Jul 2015
Emulation of Higher-Order Tensors in Manifold Monte Carlo Methods for Bayesian Inverse Problems Shiwei Lan T. Bui-Thanh M. Christie Mark Girolami 31 56 0 22 Jul 2015
Gaussian Process Regression with Location Errors D. Cervone Natesh S. Pillai 23 17 0 27 Jun 2015
Gaussian process hyper-parameter estimation using parallel asymptotically independent Markov sampling A. Garbuno-Iñigo F. DiazDelaO Konstantin Zuev 22 11 0 26 Jun 2015
Sampling constrained probability distributions using Spherical Augmentation Shiwei Lan B. Shahbaba TPM 22 14 0 19 Jun 2015
Hamiltonian Monte Carlo Acceleration Using Surrogate Functions with Random Bases Cheng Zhang B. Shahbaba Hongkai Zhao 29 32 0 18 Jun 2015