MCMC using Hamiltonian dynamics

9 June 2012

Papers citing "MCMC using Hamiltonian dynamics"

50 / 1,032 papers shown

Title
Particle-based Online Bayesian Sampling Yifan Yang Chang-rui Liu Zhengze Zhang BDL 11 7 0 28 Feb 2023
Efficient Informed Proposals for Discrete Distributions via Newton's Series Approximation Yue Xiang Dongyao Zhu Bowen Lei Dongkuan Xu Ruqi Zhang 18 5 0 27 Feb 2023
A Targeted Accuracy Diagnostic for Variational Approximations Yu-Xiang Wang Mikolaj Kasprzak Jonathan H. Huggins DRL 17 1 0 24 Feb 2023
Efficiently handling constraints with Metropolis-adjusted Langevin algorithm Jinyuan Chang C. Tang Yuanzheng Zhu 16 1 0 23 Feb 2023
Faster high-accuracy log-concave sampling via algorithmic warm starts Jason M. Altschuler Sinho Chewi 16 34 0 20 Feb 2023
Preconditioned Score-based Generative Models He Ma Xiatian Zhu Xiatian Zhu Jianfeng Feng DiffM 30 4 0 13 Feb 2023
Thermodynamic AI and the fluctuation frontier Patrick J. Coles Collin Szczepanski Denis Melanson Kaelan Donatella Antonio J. Martinez Faris M. Sbahi AI4CE 32 16 0 09 Feb 2023
On Sampling with Approximate Transport Maps Louis Grenioux Alain Durmus Eric Moulines Marylou Gabrié OT 22 15 0 09 Feb 2023
A Benchmark on Uncertainty Quantification for Deep Learning Prognostics Luis Basora Arthur Viens M. A. Chao X. Olive UQCV BDL OOD 19 8 0 09 Feb 2023
Fully Bayesian Autoencoders with Latent Sparse Gaussian Processes Ba-Hien Tran B. Shahbaba Stephan Mandt Maurizio Filippone SyDa BDL UQCV 10 5 0 09 Feb 2023
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity Vincent Souveton Arnaud Guillin J. Jasche G. Lavaux Manon Michel 16 3 0 03 Feb 2023
Versatile Energy-Based Probabilistic Models for High Energy Physics Taoli Cheng Aaron Courville DiffM 9 0 0 01 Feb 2023
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization Clément Bénard B. Staber Sébastien Da Veiga 32 4 0 31 Jan 2023
Fast Bayesian inference for spatial mean-parameterized Conway-Maxwell-Poisson models Bokgyeong Kang John Hughes M. Haran 19 1 0 27 Jan 2023
Geodesic slice sampling on the sphere Michael Habeck Mareike Hasenpflug Shantanu Kodgirwar Daniel Rudolf 8 10 0 19 Jan 2023
Physics-informed Information Field Theory for Modeling Physical Systems with Uncertainty Quantification A. Alberts Ilias Bilionis 26 12 0 18 Jan 2023
Dynamic SIR/SEIR-like models comprising a time-dependent transmission rate: Hamiltonian Monte Carlo approach with applications to COVID-19 Hristo Inouzhe María Xosé Rodríguez-Álvarez Lorenzo Nagar E. Akhmatskaya 8 4 0 16 Jan 2023
L-HYDRA: Multi-Head Physics-Informed Neural Networks Zongren Zou George Karniadakis AI4CE 16 26 0 05 Jan 2023
Design of Hamiltonian Monte Carlo for perfect simulation of general continuous distributions G. Leigh Amanda R. Northrop 19 1 0 23 Dec 2022
Parameter Inference based on Gaussian Processes Informed by Nonlinear Partial Differential Equations Zhao-Xia Li Shih-Feng Yang Jeff Wu 11 2 0 22 Dec 2022
Calibrating AI Models for Wireless Communications via Conformal Prediction K. Cohen Sangwoo Park Osvaldo Simeone S. Shamai 24 6 0 15 Dec 2022
Lower bounds on the rate of convergence for accept-reject-based Markov chains in Wasserstein and total variation distances Austin R. Brown Galin L. Jones 16 3 0 12 Dec 2022
Designing Ecosystems of Intelligence from First Principles Karl J. Friston M. Ramstead Alex B. Kiefer Alexander Tschantz Christopher L. Buckley ... K. Fung Jason G. Fox Steven Swanson D. Mapes Gabriel René 8 31 0 02 Dec 2022
Bayesian Physics Informed Neural Networks for Data Assimilation and Spatio-Temporal Modelling of Wildfires J. Dabrowski D. Pagendam J. Hilton Conrad Sanderson Dan MacKinlay C. Huston Andrew Bolt Petra Kuhnert PINN 25 17 0 02 Dec 2022
Latent Space Diffusion Models of Cryo-EM Structures Karsten Kreis Tim Dockhorn Zihao Li Ellen D. Zhong DiffM 27 15 0 25 Nov 2022
Toward Unlimited Self-Learning MCMC with Parallel Adaptive Annealing Yuma Ichikawa Akira Nakagawa Hiromoto Masayuki Yuhei Umeda BDL 18 0 0 25 Nov 2022
Neural Superstatistics for Bayesian Estimation of Dynamic Cognitive Models Lukas Schumacher Paul-Christian Burkner A. Voss Ullrich Kothe Stefan T. Radev 13 11 0 23 Nov 2022
Unadjusted Hamiltonian MCMC with Stratified Monte Carlo Time Integration Nawaf Bou-Rabee Milo Marsden 24 12 0 20 Nov 2022
Bayesian autoencoders for data-driven discovery of coordinates, governing equations and fundamental constants Liyao (Mars) Gao J. Nathan Kutz AI4CE 22 20 0 19 Nov 2022
Normalizing Flows for Hierarchical Bayesian Analysis: A Gravitational Wave Population Study David Ruhe Kaze W. K. Wong M. Cranmer Patrick Forré 11 6 0 15 Nov 2022
Bayesian score calibration for approximate models Joshua J. Bon D. Warne David J. Nott Christopher C. Drovandi 24 3 0 10 Nov 2022
Bayesian Neural Networks for Macroeconomic Analysis Niko Hauzenberger Florian Huber K. Klieber Massimiliano Marcellino BDL 29 1 0 09 Nov 2022
Sparse Gaussian Process Hyperparameters: Optimize or Integrate? V. Lalchand W. Bruinsma David R. Burt C. Rasmussen GP 17 6 0 04 Nov 2022
Nonparametric Involutive Markov Chain Monte Carlo Carol Mak Fabian Zaiser C. Ong 15 1 0 02 Nov 2022
Preferential Subsampling for Stochastic Gradient Langevin Dynamics Srshti Putcha Christopher Nemeth Paul Fearnhead 17 0 0 28 Oct 2022
ProbNeRF: Uncertainty-Aware Inference of 3D Shapes from 2D Images Matthew D. Hoffman T. Le Pavel Sountsov Christopher Suter Ben Lee Vikash K. Mansinghka Rif A. Saurous BDL 24 12 0 27 Oct 2022
SPQR: An R Package for Semi-Parametric Density and Quantile Regression Steven G. Xu Reetam Majumder Brian J. Reich 11 0 0 26 Oct 2022
Sampling with Mollified Interaction Energy Descent Lingxiao Li Qiang Liu Anna Korba Mikhail Yurochkin Justin Solomon 25 15 0 24 Oct 2022
On Many-Actions Policy Gradient Michal Nauman Marek Cygan 9 0 0 24 Oct 2022
Online Probabilistic Model Identification using Adaptive Recursive MCMC Pedram Agand Mo Chen H. Taghirad 27 4 0 23 Oct 2022
Adaptive Tuning for Metropolis Adjusted Langevin Trajectories L. Riou-Durand Pavel Sountsov Jure Vogrinc C. Margossian Samuel Power 25 6 0 21 Oct 2022
Unbiased constrained sampling with Self-Concordant Barrier Hamiltonian Monte Carlo Maxence Noble Valentin De Bortoli Alain Durmus 16 6 0 21 Oct 2022
Transport Elliptical Slice Sampling A. Cabezas Christopher Nemeth 11 8 0 19 Oct 2022
Estimating the Contamination Factor's Distribution in Unsupervised Anomaly Detection Lorenzo Perini Paul-Christian Buerkner Arto Klami 18 14 0 19 Oct 2022
Sampling using Adaptive Regenerative Processes Hector McKimm Andi Q. Wang M. Pollock Christian P. Robert Gareth O. Roberts 16 1 0 18 Oct 2022
ZooD: Exploiting Model Zoo for Out-of-Distribution Generalization Qishi Dong Muhammad Awais Fengwei Zhou Chuanlong Xie Tianyang Hu Yongxin Yang Sung-Ho Bae Zhenguo Li OODD VLM 18 14 0 17 Oct 2022
Data Subsampling for Bayesian Neural Networks Eiji Kawasaki M. Holzmann BDL 17 1 0 17 Oct 2022
Principled Pruning of Bayesian Neural Networks through Variational Free Energy Minimization Jim Beckers Bart Van Erp Ziyue Zhao K. Kondrashov Bert De Vries AAML 21 5 0 17 Oct 2022
Meta-Uncertainty in Bayesian Model Comparison Marvin Schmitt Stefan T. Radev Paul-Christian Burkner UD 22 10 0 13 Oct 2022
Maximum entropy exploration in contextual bandits with neural networks and energy based models A. Elwood Marco Leonardi A. Mohamed A. Rozza 8 1 0 12 Oct 2022