Results 1 to 10 of about 29,218,878 (175)
On the Anatomy of MCMC-Based Maximum Likelihood Learning of Energy-Based Models [PDF]
AAAI Conference on Artificial Intelligence, 2019 This study investigates the effects of Markov chain Monte Carlo (MCMC) sampling in unsupervised Maximum Likelihood (ML) learning. Our attention is restricted to the family of unnormalized probability densities for which the negative log density (or ...
Han, Tian +4 more
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Point Cloud Registration Based on MCMC-SA ICP Algorithm
IEEE Access, 2019 Point cloud registration is very important for workpiece positioning and error evaluation. Generally, the Iterative Closest Points (ICP) algorithm is always adopted as the first choice in fine registration, but requires a more appropriate initial ...
Haibo Liu +5 more
doaj +2 more sources
Quantum annealing enhanced Markov-Chain Monte Carlo [PDF]
Scientific ReportsIn this study, we propose quantum annealing-enhanced Markov Chain Monte Carlo (QAEMCMC), where QA is integrated into the MCMC subroutine. QA efficiently explores low-energy configurations and overcomes local minima, enabling the generation of proposal ...
Shunta Arai, Tadashi Kadowaki
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Statistica, 2021 Based on the hybrid censored samples, this article deals with the problem of point and interval estimation of the stress-strength reliability R = P(Y < X) when X and Y both have independent generalized inverted exponential distributions with different ...
Renu Garg, Kapil Kumar
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Statistica, 2021 In this paper we deal with the modelling of cumulative incidence function using improper Gompertz distribution based on middle censored competing risks survival data. Together with the unknown parameters, cumulative incidence function also estimated.
Habbiburr Rehman, Navin Chandra
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Multilevel Delayed Acceptance MCMC [PDF]
SIAM/ASA J. Uncertain. Quantification, 2022 We develop a novel Markov chain Monte Carlo (MCMC) method that exploits a hierarchy of models of increasing complexity to efficiently generate samples from an unnormalized target distribution.
M. Lykkegaard +4 more
semanticscholar +1 more source
Unbiased Multilevel Monte Carlo methods for intractable distributions: MLMC meets MCMC [PDF]
Journal of machine learning research, 2022 Constructing unbiased estimators from Markov chain Monte Carlo (MCMC) outputs is a difficult problem that has recently received a lot of attention in the statistics and machine learning communities. However, the current unbiased MCMC framework only works
Guanyang Wang, T. Wang
semanticscholar +1 more source
Parameter estimation for X-ray scattering analysis with Hamiltonian Markov Chain Monte Carlo
Journal of Synchrotron Radiation, 2022 Bayesian-inference-based approaches, in particular the random-walk Markov Chain Monte Carlo (MCMC) method, have received much attention recently for X-ray scattering analysis.
Zhang Jiang +4 more
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A Bayesian Estimation and Predictionof Gompertz Extension Distribution Using the MCMC Method
, 2020 In this paper, the Markov chain Monte Carlo (MCMC) method is used to estimate the parameters of the Gompertz extension distribution based on a complete sample.
A. Chaudhary, Vijay Kumar
semanticscholar +1 more source
Neural Langevin Dynamical Sampling
IEEE Access, 2020 Sampling technique is one of the asymptotically unbiased estimation approaches for inference in Bayesian probabilistic models. Markov chain Monte Carlo (MCMC) is a kind of sampling methods, which is widely used in the inference of complex probabilistic ...
Minghao Gu, Shiliang Sun
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