MCMC using Hamiltonian dynamics

9 June 2012

Papers citing "MCMC using Hamiltonian dynamics"

50 / 1,031 papers shown

Title
Generative Modeling by Inclusive Neural Random Fields with Applications in Image Generation and Anomaly Detection Yunfu Song Zhijian Ou DiffM 6 30 0 01 Jun 2018
Bayesian Pose Graph Optimization via Bingham Distributions and Tempered Geodesic MCMC Tolga Birdal Umut Simsekli M. Eken Slobodan Ilic 9 38 0 31 May 2018
Hamiltonian Variational Auto-Encoder Anthony L. Caterini Arnaud Doucet Dino Sejdinovic BDL DRL 11 94 0 29 May 2018
Bayesian Learning with Wasserstein Barycenters Julio D. Backhoff Veraguas J. Fontbona Gonzalo Rios Felipe A. Tobar 15 29 0 28 May 2018
Ergodic Inference: Accelerate Convergence by Optimisation Yichuan Zhang José Miguel Hernández-Lobato BDL 11 9 0 25 May 2018
Langevin Markov Chain Monte Carlo with stochastic gradients Charles Matthews J. Weare BDL 6 6 0 22 May 2018
Sampling-Free Variational Inference of Bayesian Neural Networks by Variance Backpropagation Manuel Haussmann Fred Hamprecht M. Kandemir BDL 13 6 0 19 May 2018
Semi-parametric Bayesian change-point model based on the Dirichlet process G. Mastrantonio 11 0 0 16 May 2018
Improving Predictive Uncertainty Estimation using Dropout -- Hamiltonian Monte Carlo Diego Vergara S. Hernández Matias Valdenegro-Toro Felipe Jorquera UQCV BDL 9 0 0 12 May 2018
Subsampling Sequential Monte Carlo for Static Bayesian Models David Gunawan Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran 11 46 0 08 May 2018
Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands Rohitash Chandra Danial Azam R. Müller T. Salles Sally Cripps 19 20 0 02 May 2018
Coupling and Convergence for Hamiltonian Monte Carlo Nawaf Bou-Rabee A. Eberle Raphael Zimmer 73 136 0 01 May 2018
Persistent Monitoring of Stochastic Spatio-temporal Phenomena with a Small Team of Robots S. Garg Nora Ayanian 18 28 0 27 Apr 2018
Nonparametric Bayesian label prediction on a large graph using truncated Laplacian regularization Jarno Hartog Harry Van Zanten 9 3 0 13 Apr 2018
Motor Unit Number Estimation via Sequential Monte Carlo S. Taylor Chris Sherlock Gareth Ridall Paul Fearnhead 23 1 0 11 Apr 2018
Accelerating MCMC Algorithms Christian P. Robert Victor Elvira Nicholas G. Tawn Changye Wu 12 140 0 08 Apr 2018
Hamiltonian Monte Carlo for Probabilistic Programs with Discontinuities Bradley Gram-Hansen Yuanshuo Zhou Tobias Kohn Tom Rainforth Hongseok Yang Frank D. Wood 8 3 0 07 Apr 2018
Frequency violations from random disturbances: an MCMC approach John Moriarty Jure Vogrinc Alessandro Zocca 14 7 0 22 Mar 2018
Building a Telescope to Look Into High-Dimensional Image Spaces Mitch Hill Erik Nijkamp Song-Chun Zhu DiffM 13 9 0 02 Mar 2018
Analysis of Langevin Monte Carlo via convex optimization Alain Durmus Szymon Majewski B. Miasojedow 27 216 0 26 Feb 2018
Sampling as optimization in the space of measures: The Langevin dynamics as a composite optimization problem Andre Wibisono 13 177 0 22 Feb 2018
Neural Network Renormalization Group Shuo-Hui Li Lei Wang BDL DRL 21 126 0 08 Feb 2018
Bayesian Coreset Construction via Greedy Iterative Geodesic Ascent Trevor Campbell Tamara Broderick 12 136 0 05 Feb 2018
Embedded Model Error Representation for Bayesian Model Calibration K. Sargsyan Xun Huan H. Najm 28 45 0 21 Jan 2018
Log-concave sampling: Metropolis-Hastings algorithms are fast Raaz Dwivedi Yuansi Chen Martin J. Wainwright Bin Yu 23 250 0 08 Jan 2018
Deterministic Sampling of Expensive Posteriors Using Minimum Energy Designs V. R. Joseph Dianpeng Wang Li Gu Shiji Lyu Rui Tuo 11 36 0 24 Dec 2017
Wave function representation of probability distributions Madeleine B. Thompson 13 1 0 21 Dec 2017
Noisy Natural Gradient as Variational Inference Guodong Zhang Shengyang Sun D. Duvenaud Roger C. Grosse ODL 16 210 0 06 Dec 2017
A trans-disciplinary review of deep learning research for water resources scientists Chaopeng Shen AI4CE 25 681 0 06 Dec 2017
Thermostat-assisted continuously-tempered Hamiltonian Monte Carlo for Bayesian learning Rui Luo Jianhong Wang Yaodong Yang Zhanxing Zhu Jun Wang 12 13 0 30 Nov 2017
Informed proposals for local MCMC in discrete spaces Giacomo Zanella 20 121 0 20 Nov 2017
Non-reversible, tuning- and rejection-free Markov chain Monte Carlo via iterated random functions A. Sepehri J. Marković 16 4 0 20 Nov 2017
Advances in Variational Inference Cheng Zhang Judith Butepage Hedvig Kjellström Stephan Mandt BDL 36 684 0 15 Nov 2017
Kernel Conditional Exponential Family Michael Arbel A. Gretton 15 25 0 15 Nov 2017
Geometric integrators and the Hamiltonian Monte Carlo method Nawaf Bou-Rabee J. Sanz-Serna 20 97 0 14 Nov 2017
Adaptive Bayesian Sampling with Monte Carlo EM A. Roychowdhury S. Parthasarathy 27 1 0 06 Nov 2017
Inversion using a new low-dimensional representation of complex binary geological media based on a deep neural network E. Laloy Romain Hérault J. Lee D. Jacques N. Linde 16 192 0 25 Oct 2017
Zero Variance and Hamiltonian Monte Carlo Methods in GARCH Models Rafael S. Paixão R. Ehlers 15 1 0 20 Oct 2017
Finite-dimensional Gaussian approximation with linear inequality constraints A. F. López-Lopera F. Bachoc N. Durrande O. Roustant 9 67 0 20 Oct 2017
Convergence Rate of Riemannian Hamiltonian Monte Carlo and Faster Polytope Volume Computation Y. Lee Santosh Vempala 28 113 0 17 Oct 2017
Data analysis recipes: Using Markov Chain Monte Carlo D. Hogg D. Foreman-Mackey 14 206 0 17 Oct 2017
Automated Scalable Bayesian Inference via Hilbert Coresets Trevor Campbell Tamara Broderick 19 127 0 13 Oct 2017
Bayesian Hypernetworks David M. Krueger Chin-Wei Huang Riashat Islam Ryan Turner Alexandre Lacoste Aaron Courville UQCV BDL 17 139 0 13 Oct 2017
sgmcmc: An R Package for Stochastic Gradient Markov Chain Monte Carlo Jack Baker Paul Fearnhead E. Fox Christopher Nemeth BDL 24 11 0 02 Oct 2017
Learning Energy-Based Models as Generative ConvNets via Multi-grid Modeling and Sampling Ruiqi Gao Yang Lu Junpei Zhou Song-Chun Zhu Ying Nian Wu 24 78 0 26 Sep 2017
Hamiltonian Flow Simulation of Rare Events R. Douady Shohruh Miryusupov 33 0 0 05 Sep 2017
Unbiased Hamiltonian Monte Carlo with couplings J. Heng Pierre E. Jacob 16 63 0 01 Sep 2017
Earth System Modeling 2.0: A Blueprint for Models That Learn From Observations and Targeted High-Resolution Simulations T. Schneider Shiwei Lan Andrew M. Stuart J. Teixeira AI4Cl 19 313 0 31 Aug 2017
BAMBI: An R package for Fitting Bivariate Angular Mixture Models Saptarshi Chakraborty Samuel W. K. Wong 25 16 0 25 Aug 2017
Rapid Mixing of Hamiltonian Monte Carlo on Strongly Log-Concave Distributions Oren Mangoubi Aaron Smith 27 106 0 23 Aug 2017