v1v2v3 (latest)

Hamiltonian Monte Carlo with Energy Conserving Subsampling

2 August 2017

Papers citing "Hamiltonian Monte Carlo with Energy Conserving Subsampling"

23 / 23 papers shown

Title
Bayesian neural networks with interpretable priors from Mercer kernels A. Alberts Ilias Bilionis UQCV BDL 228 0 0 27 Oct 2025
Uncertainty Quantification of Graph Convolution Neural Network Models of Evolving Processes J. Hauth Cosmin Safta Xun Huan Ravi G. Patel Reese E. Jones BDL UQCV 248 2 0 17 Feb 2024
Optimal subsampling for large scale Elastic-net regression Hang Yu Zhenxing Dou Zhiwei Chen Xiaomeng Yan 144 0 0 24 May 2023
Bayes Hilbert Spaces for Posterior Approximation George Wynne 179 2 0 18 Apr 2023
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty QuantificationJournal of Computational Physics (JCP), 2023 A. Alberts Ilias Bilionis 306 16 0 18 Jan 2023
Grassmann Stein Variational Gradient DescentInternational Conference on Artificial Intelligence and Statistics (AISTATS), 2022 Xingtu Liu Harrison Zhu Jean-François Ton George Wynne Andrew Duncan 249 13 0 07 Feb 2022
Metropolis Augmented Hamiltonian Monte Carlo Guangyao Zhou 204 2 0 20 Jan 2022
Surrogate Likelihoods for Variational Annealed Importance SamplingInternational Conference on Machine Learning (ICML), 2021 M. Jankowiak Du Phan BDL 185 13 0 22 Dec 2021
Spectral Subsampling MCMC for Stationary Multivariate Time Series with Applications to Vector ARTFIMA ProcessesEconometrics and Statistics (ES), 2021 M. Villani M. Quiroz Robert Kohn R. Salomone AI4TS 130 9 0 05 Apr 2021
On MCMC for variationally sparse Gaussian processes: A pseudo-marginal approach Karla Monterrubio-Gómez S. Wade 128 2 0 04 Mar 2021
Truncated Log-concave Sampling with Reflective Hamiltonian Monte CarloACM Transactions on Mathematical Software (TOMS), 2021 Apostolos Chalkis Vissarion Fisikopoulos Marios Papachristou Elias P. Tsigaridas 219 8 0 25 Feb 2021
Laplacian Smoothing Stochastic Gradient Markov Chain Monte CarloSIAM Journal on Scientific Computing (SISC), 2019 Bao Wang Difan Zou Quanquan Gu Stanley Osher BDL 84 9 0 02 Nov 2019
Spectral Subsampling MCMC for Stationary Time SeriesInternational Conference on Machine Learning (ICML), 2019 R. Salomone M. Quiroz Robert Kohn M. Villani Minh-Ngoc Tran AI4TS 192 15 0 30 Oct 2019
Aggregated Gradient Langevin DynamicsAAAI Conference on Artificial Intelligence (AAAI), 2019 Chao Zhang Jiahao Xie Zebang Shen P. Zhao Tengfei Zhou Hui Qian 185 1 0 21 Oct 2019
Distributed Computation for Marginal Likelihood based Model ChoiceBayesian Analysis (BA), 2019 Alexander K. Buchholz Daniel Ahfock S. Richardson FedML 272 5 0 10 Oct 2019
Stochastic Gradient Hamiltonian Monte Carlo for Non-Convex Learning Huy N. Chau M. Rásonyi 135 12 0 25 Mar 2019
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets R. Cornish Paul Vanetti Alexandre Bouchard-Côté George Deligiannidis Arnaud Doucet 208 20 0 28 Jan 2019
Targeted stochastic gradient Markov chain Monte Carlo for hidden Markov models with rare latent states Rihui Ou Deborshee Sen Alexander L. Young David B. Dunson BDL 126 0 0 31 Oct 2018
Subsampling MCMC - An introduction for the survey statistician M. Quiroz M. Villani Robert Kohn Minh-Ngoc Tran Khue-Dung Dang 228 24 0 23 Jul 2018
Subsampling Sequential Monte Carlo for Static Bayesian Models David Gunawan Khue-Dung Dang M. Quiroz Robert Kohn Minh-Ngoc Tran 254 52 0 08 May 2018
Pseudo-Marginal Hamiltonian Monte CarloJournal of machine learning research (JMLR), 2016 Johan Alenlöv Arnaud Doucet Fredrik Lindsten 168 23 0 08 Jul 2016
The block-Poisson estimator for optimally tuned exact subsampling MCMC M. Quiroz Minh-Ngoc Tran M. Villani Robert Kohn Khue-Dung Dang 328 27 0 27 Mar 2016
Speeding Up MCMC by Efficient Data SubsamplingJournal of the American Statistical Association (JASA), 2014 M. Quiroz Robert Kohn M. Villani Minh-Ngoc Tran 335 179 0 16 Apr 2014