The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo

18 November 2011

Matthew D. Hoffman

Papers citing "The No-U-Turn Sampler: Adaptively Setting Path Lengths in Hamiltonian Monte Carlo"

32 / 32 papers shown

Title
JaxSGMC: Modular stochastic gradient MCMC in JAX Stephan Thaler Paul Fuchs Ana Cukarska Julija Zavadlav BDL 128 2 0 16 May 2025
Humble your Overconfident Networks: Unlearning Overfitting via Sequential Monte Carlo Tempered Deep Ensembles Andrew Millard Zheng Zhao Joshua Murphy Simon Maskell UQCV BDL 60 0 0 16 May 2025
New affine invariant ensemble samplers and their dimensional scaling Yifan Chen 78 0 0 05 May 2025
Improving the evaluation of samplers on multi-modal targets Louis Grenioux Maxence Noble Marylou Gabrié 345 0 0 11 Apr 2025
IAEmu: Learning Galaxy Intrinsic Alignment Correlations Sneh Pandya Yuanyuan Yang N. V. Alfen Jonathan Blazek Robin Walters 68 1 0 07 Apr 2025
CreINNs: Credal-Set Interval Neural Networks for Uncertainty Estimation in Classification Tasks Kaizheng Wang Keivan K1 Shariatmadar Shireen Kudukkil Manchingal Fabio Cuzzolin David Moens Hans Hallez UQCV BDL 175 13 0 28 Jan 2025
From discrete-time policies to continuous-time diffusion samplers: Asymptotic equivalences and faster training Julius Berner Lorenz Richter Marcin Sendera Jarrid Rector-Brooks Nikolay Malkin OffRL 91 7 0 10 Jan 2025
Inflationary Flows: Calibrated Bayesian Inference with Diffusion-Based Models Daniela de Albuquerque John Pearson DiffM 84 0 0 03 Jan 2025
Improving Pareto Set Learning for Expensive Multi-objective Optimization via Stein Variational Hypernetworks Minh-Duc Nguyen Phuong Mai Dinh Quang-Huy Nguyen L. P. Hoang Dung D. Le 81 1 0 23 Dec 2024
Cautious Optimizers: Improving Training with One Line of Code Kaizhao Liang Lizhang Chen B. Liu Qiang Liu ODL 143 8 0 25 Nov 2024
Hamiltonian Monte Carlo Inference of Marginalized Linear Mixed-Effects Models Jinlin Lai Justin Domke Daniel Sheldon 71 0 0 31 Oct 2024
Noise-Aware Differentially Private Variational Inference Talal Alrawajfeh Hibiki Ito Antti Honkela 90 0 0 25 Oct 2024
Learned Reference-based Diffusion Sampling for multi-modal distributions Maxence Noble Louis Grenioux Marylou Gabrié Alain Durmus DiffM 65 3 0 25 Oct 2024
AutoStep: Locally adaptive involutive MCMC Tiange Liu Nikola Surjanovic Miguel Biron-Lattes Alexandre Bouchard-Côté Trevor Campbell 48 1 0 24 Oct 2024
Predictive variational inference: Learn the predictively optimal posterior distribution Jinlin Lai Yuling Yao BDL 50 0 0 18 Oct 2024
Bayesian Experimental Design via Contrastive Diffusions Jacopo Iollo Christophe Heinkelé Pierre Alliez Florence Forbes 73 0 0 15 Oct 2024
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation Matrix C. Margossian Lawrence K. Saul 64 1 0 14 Oct 2024
Can We Predict Performance of Large Models across Vision-Language Tasks? Qinyu Zhao Ming Xu Kartik Gupta Akshay Asthana Liang Zheng Stephen Gould 70 0 0 14 Oct 2024
Implicit Dynamical Flow Fusion (IDFF) for Generative Modeling Mohammad R. Rezaei Rahul G. Krishnan Milos R. Popovic M. Lankarany DiffM 45 0 0 22 Sep 2024
Inverse decision-making using neural amortized Bayesian actors Dominik Straub Tobias F. Niehues Jan Peters Constantin Rothkopf 93 1 0 04 Sep 2024
Gradient-free variational learning with conditional mixture networks Conor Heins Hao Wu Dimitrije Marković Alexander Tschantz Jeff Beck Christopher L. Buckley BDL 59 3 0 29 Aug 2024
Randomized Transport Plans via Hierarchical Fully Probabilistic Design Sarah Boufelja Anthony Quinn Robert Shorten OT 71 0 0 04 Aug 2024
Importance Corrected Neural JKO Sampling Johannes Hertrich Robert Gruhlke 78 2 0 29 Jul 2024
Scalable Bayesian Learning with posteriors Samuel Duffield Kaelan Donatella Johnathan Chiu Phoebe Klett Daniel Simpson BDL UQCV 92 1 0 31 May 2024
Variational Bayesian Optimal Experimental Design with Normalizing Flows Jiayuan Dong Christian L. Jacobsen Mehdi Khalloufi Maryam Akram Wanjiao Liu Karthik Duraisamy Xun Huan BDL 95 7 0 08 Apr 2024
Variational Inference for Uncertainty Quantification: an Analysis of Trade-offs C. Margossian Loucas Pillaud-Vivien Lawrence K. Saul UD 102 2 0 20 Mar 2024
Improved off-policy training of diffusion samplers Marcin Sendera Minsu Kim Sarthak Mittal Pablo Lemos Luca Scimeca Jarrid Rector-Brooks Alexandre Adam Yoshua Bengio Nikolay Malkin OffRL 86 22 0 07 Feb 2024
Uncertainty Quantification and Propagation in Surrogate-based Bayesian Inference Philipp Reiser Javier Enrique Aguilar A. Guthke Paul-Christian Bürkner 53 2 0 08 Dec 2023
Towards Understanding Sycophancy in Language Models Mrinank Sharma Meg Tong Tomasz Korbak David Duvenaud Amanda Askell ... Oliver Rausch Nicholas Schiefer Da Yan Miranda Zhang Ethan Perez 257 211 0 20 Oct 2023
Fitting Bayesian item response models in Stata and Stan Robert Grant Daniel Furr Bob Carpenter Andrew Gelman 159 17 0 13 Jan 2016
Distributed Bayesian Learning with Stochastic Natural-gradient Expectation Propagation and the Posterior Server Leonard Hasenclever Stefan Webb Thibaut Lienart Sebastian J. Vollmer Balaji Lakshminarayanan Charles Blundell Yee Whye Teh BDL 83 70 0 31 Dec 2015
MCMC using Hamiltonian dynamics Radford M. Neal 285 3,278 0 09 Jun 2012