MCMC using Hamiltonian dynamics

9 June 2012

Papers citing "MCMC using Hamiltonian dynamics"

50 / 1,032 papers shown

Title
On Divergence Measures for Bayesian Pseudocoresets Balhae Kim J. Choi Seanie Lee Yoonho Lee Jung-Woo Ha Juho Lee DD 8 11 0 12 Oct 2022
Gradient-Guided Importance Sampling for Learning Binary Energy-Based Models Meng Liu Haoran Liu Shuiwang Ji 22 5 0 11 Oct 2022
Deep Active Ensemble Sampling For Image Classification S. Mohamadi Gianfranco Doretto Donald Adjeroh UQCV 13 9 0 11 Oct 2022
Robust and Controllable Object-Centric Learning through Energy-based Models Ruixiang Zhang Tong Che B. Ivanovic Renhao Wang Marco Pavone Yoshua Bengio Liam Paull OCL 26 8 0 11 Oct 2022
CoopHash: Cooperative Learning of Multipurpose Descriptor and Contrastive Pair Generator via Variational MCMC Teaching for Supervised Image Hashing Khoa D. Doan Jianwen Xie Y. Zhu Yang Zhao Ping Li GAN 10 2 0 09 Oct 2022
Automatic Data Augmentation via Invariance-Constrained Learning Ignacio Hounie Luiz F. O. Chamon Alejandro Ribeiro 18 10 0 29 Sep 2022
Denoising MCMC for Accelerating Diffusion-Based Generative Models Beomsu Kim Jong Chul Ye DiffM 44 13 0 29 Sep 2022
Marginally Constrained Nonparametric Bayesian Inference through Gaussian Processes Bingjing Tang Vinayak A. Rao 6 0 0 28 Sep 2022
Hamiltonian Adaptive Importance Sampling Ali Mousavi R. Monsefi Victor Elvira 28 13 0 27 Sep 2022
Hamiltonian Monte Carlo for efficient Gaussian sampling: long and random steps Simon Apers S. Gribling Dániel Szilágyi 26 10 0 26 Sep 2022
Face Super-Resolution Using Stochastic Differential Equations Marcelo dos Santos Rayson Laroca Rafael O. Ribeiro João Neves Hugo Proencca David Menotti DiffM 24 11 0 24 Sep 2022
hdtg: An R package for high-dimensional truncated normal simulation Zhenyu Zhang A. Chin A. Nishimura M. Suchard 11 2 0 23 Sep 2022
Amortized Variational Inference: A Systematic Review Ankush Ganguly Sanjana Jain Ukrit Watchareeruetai 15 14 0 22 Sep 2022
Seq2Seq Surrogates of Epidemic Models to Facilitate Bayesian Inference G. Charles Timothy M Wolock P. Winskill A. Ghani Samir Bhatt Seth Flaxman 13 4 0 20 Sep 2022
Physics-Informed Machine Learning of Dynamical Systems for Efficient Bayesian Inference Somayajulu L. N. Dhulipala Yifeng Che Michael D. Shields 28 0 0 19 Sep 2022
Optimal Scaling for Locally Balanced Proposals in Discrete Spaces Haoran Sun H. Dai Dale Schuurmans 18 13 0 16 Sep 2022
Efficiency Ordering of Stochastic Gradient Descent Jie Hu Vishwaraj Doshi Do Young Eun 26 6 0 15 Sep 2022
A Geometric Perspective on Variational Autoencoders Clément Chadebec S. Allassonnière DRL 24 21 0 15 Sep 2022
Langevin Autoencoders for Learning Deep Latent Variable Models Shohei Taniguchi Yusuke Iwasawa Wataru Kumagai Yutaka Matsuo BDL SyDa 36 2 0 15 Sep 2022
BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data Ka-Yee Tung Steven De La Torre Mohamed El Mistiri Rebecca Braga De Braganca Eric B. Hekler Misha Pavel D. Rivera Pedja Klasnja D. Spruijt-Metz Benjamin M. Marlin 17 1 0 12 Sep 2022
Parallel MCMC Algorithms: Theoretical Foundations, Algorithm Design, Case Studies N. Glatt-Holtz Andrew J Holbrook J. Krometis Cecilia F. Mondaini 16 10 0 10 Sep 2022
SE(3)-DiffusionFields: Learning smooth cost functions for joint grasp and motion optimization through diffusion Julen Urain Niklas Funk Jan Peters Georgia Chalvatzaki DiffM 52 118 0 08 Sep 2022
Bayesian Neural Network Inference via Implicit Models and the Posterior Predictive Distribution J. Dabrowski D. Pagendam UQCV BDL 11 0 0 06 Sep 2022
elhmc: An R Package for Hamiltonian Monte Carlo Sampling in Bayesian Empirical Likelihood Dang Trung Kien Neo Han Wei S. Chaudhuri 17 2 0 02 Sep 2022
Bayesian order identification of ARMA models with projection predictive inference Yann McLatchie Asael Alonzo Matamoros David Kohns Aki Vehtari 10 1 0 31 Aug 2022
Smoothness Analysis for Probabilistic Programs with Application to Optimised Variational Inference Wonyeol Lee Xavier Rival Hongseok Yang 14 9 0 22 Aug 2022
Score-Based Diffusion meets Annealed Importance Sampling Arnaud Doucet Will Grathwohl A. G. Matthews Heiko Strathmann DiffM 28 43 0 16 Aug 2022
Nesterov smoothing for sampling without smoothness JiaoJiao Fan Bo Yuan Jiaming Liang Yongxin Chen 32 2 0 15 Aug 2022
Intuitive Joint Priors for Bayesian Linear Multilevel Models: The R2D2M2 prior Javier Enrique Aguilar Paul-Christian Burkner 9 24 0 15 Aug 2022
Bayesian Inference with Latent Hamiltonian Neural Networks Somayajulu L. N. Dhulipala Yifeng Che Michael D. Shields BDL 29 3 0 12 Aug 2022
Sampling algorithms in statistical physics: a guide for statistics and machine learning Michael F Faulkner Samuel Livingstone 11 6 0 09 Aug 2022
Computing Bayes: From Then 'Til Now' G. Martin David T. Frazier Christian P. Robert 20 15 0 01 Aug 2022
Sliced Wasserstein Variational Inference Mingxuan Yi Song Liu 17 19 0 26 Jul 2022
A Bayesian hierarchical framework for emulating a complex crop yield simulator M. M. Hasan J. Cumming 17 0 0 26 Jul 2022
Efficient shape-constrained inference for the autocovariance sequence from a reversible Markov chain Stephen Berg Hyebin Song 25 6 0 26 Jul 2022
Uncertainty Calibration in Bayesian Neural Networks via Distance-Aware Priors Gianluca Detommaso Alberto Gasparin A. Wilson Cédric Archambeau UQCV BDL 29 3 0 17 Jul 2022
Split Hamiltonian Monte Carlo revisited F. Casas J. Sanz-Serna Luke Shaw 11 8 0 15 Jul 2022
BR-SNIS: Bias Reduced Self-Normalized Importance Sampling Gabriel Victorino Cardoso S. Samsonov Achille Thin Eric Moulines Jimmy Olsson 24 6 0 13 Jul 2022
On the Robustness of Bayesian Neural Networks to Adversarial Attacks Luca Bortolussi Ginevra Carbone Luca Laurenti A. Patané G. Sanguinetti Matthew Wicker AAML 16 11 0 13 Jul 2022
Expert Elicitation and Data Noise Learning for Material Flow Analysis using Bayesian Inference Jiayuan Dong Jiankan Liao Xun Huan Daniel R. Cooper 9 6 0 13 Jul 2022
Accelerating Score-based Generative Models with Preconditioned Diffusion Sampling He Ma Li Zhang Xiatian Zhu Jianfeng Feng DiffM 84 25 0 05 Jul 2022
Accelerating Hamiltonian Monte Carlo via Chebyshev Integration Time Jun-Kun Wang Andre Wibisono 22 9 0 05 Jul 2022
Cyclical Kernel Adaptive Metropolis J. Li Yimeng Zeng Wen-Ping Guo 6 0 0 29 Jun 2022
Reconstructing the Universe with Variational self-Boosted Sampling Chirag Modi Yin Li David M. Blei 11 8 0 28 Jun 2022
Robustness to corruption in pre-trained Bayesian neural networks Xi Wang Laurence Aitchison OOD UQCV 9 4 0 24 Jun 2022
Automatic Zig-Zag sampling in practice Alice Corbella S. Spencer Gareth O. Roberts 8 20 0 22 Jun 2022
A Langevin-like Sampler for Discrete Distributions Ruqi Zhang Xingchao Liu Qiang Liu BDL 16 37 0 20 Jun 2022
Low-Precision Stochastic Gradient Langevin Dynamics Ruqi Zhang A. Wilson Chris De Sa BDL 8 14 0 20 Jun 2022
Approximate Bayesian Inference for the Interaction Types 1, 2, 3 and 4 with Application in Disease Mapping Esmail Abdul Fattah Haavard Rue 8 6 0 18 Jun 2022
Iterative importance sampling with Markov chain Monte Carlo sampling in robust Bayesian analysis Ivette Raices Cruz J. Lindström Matthias C. M. Troffaes U. Sahlin 19 12 0 17 Jun 2022