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"

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Title
Reliability Analysis of Complex Systems using Subset Simulations with Hamiltonian Neural Networks Denny Thaler Somayajulu L. N. Dhulipala F. Bamer Bernd Markert Michael D. Shields 29 7 0 10 Jan 2024
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Data-driven Prior Learning for Bayesian Optimisation Sigrid Passano Hellan Christopher G. Lucas Nigel H. Goddard 21 0 0 24 Nov 2023
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Beyond Bayesian Model Averaging over Paths in Probabilistic Programs with Stochastic Support Tim Reichelt C.-H. Luke Ong Tom Rainforth 22 0 0 23 Oct 2023
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A representation learning approach to probe for dynamical dark energy in matter power spectra Davide Piras Lucas Lombriser 14 2 0 16 Oct 2023
On the Properties and Estimation of Pointwise Mutual Information Profiles Paweł Czyż Frederic Grabowski Julia E. Vogt N. Beerenwinkel Alexander Marx 19 1 0 16 Oct 2023
Posterior Sampling-based Online Learning for Episodic POMDPs Dengwang Tang Dongze Ye Rahul Jain A. Nayyar Pierluigi Nuzzo OffRL 42 0 0 16 Oct 2023
An Introduction to the Calibration of Computer Models Richard D. Wilkinson Christopher W. Lanyon 24 0 0 13 Oct 2023
Bayesian inference and cure rate modeling for event history data Panagiotis Papastamoulis Fotios Milienos 8 3 0 10 Oct 2023
Dynamical versus Bayesian Phase Transitions in a Toy Model of Superposition Zhongtian Chen Edmund Lau Jake Mendel Susan Wei Daniel Murfet 14 13 0 10 Oct 2023
Multi-fidelity No-U-Turn Sampling Kislaya Ravi T. Neckel H. Bungartz 17 1 0 04 Oct 2023
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Exact and Efficient Bayesian Inference for Privacy Risk Quantification (Extended Version) Rasmus C. Rønneberg Raúl Pardo Andrzej Wasowski 4 0 0 31 Aug 2023
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Learning variational autoencoders via MCMC speed measures Marcel Hirt Vasileios Kreouzis P. Dellaportas BDL DRL 13 2 0 26 Aug 2023
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