Results 121 to 130 of about 2,604,808 (287)
Bayesian Trend Filtering via Proximal Markov Chain Monte Carlo. [PDF]
J Comput Graph Stat, 2023 Heng Q, Zhou H, Chi EC.
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Parallel Markov Chain Monte Carlo [PDF]
The increasing availability of multi-core and multi-processor architectures provides\ud new opportunities for improving the performance of many computer simulations.\ud Markov Chain Monte Carlo (MCMC) simulations are widely used for approximate\ud counting problems, Bayesian inference and as a means for estimating very highdimensional\ud integrals.
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Limnology and Oceanography: Methods, EarlyView.Abstract Tailwaters are ubiquitous and highly managed ecosystems whose food webs often rely disproportionately on autochthonous energy. In situ continuous dissolved oxygen data are increasingly being used to estimate gross primary productivity and ecosystem respiration in rivers, but this approach is complicated in tailwaters, where upriver ...
Ian W. Bishop +5 more
wiley +1 more source
IsoFrog: a reversible jump Markov Chain Monte Carlo feature selection-based method for predicting isoform functions. [PDF]
Bioinformatics, 2023 Liu Y, Yang C, Li HD, Wang J.
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Predicting Statistical Signatures of Collective Emission in Disordered Color Center Ensembles
Laser &Photonics Reviews, EarlyView.We present an efficient simulation framework for modeling collective emission in disordered ensembles of quantum emitters. The low computational complexity enables large‐scale Monte Carlo simulations. Applied to SiV−${\rm SiV}^{-}$ clusters, it predicts thresholded superradiant bursts set by emitter number and quantum efficiency, as well as interaction‐
Qingyi Zhou +4 more
wiley +1 more source
Psychology &Marketing, EarlyView.ABSTRACT Sustainability information is difficult for consumers to evaluate because environmental performance represents a credence attribute. Although numerical sustainability claims have been shown to improve consumers' perceptions of sustainability communication, little is known about whether they influence product choice under realistic marketplace ...
Elena Gasulla Tortajada +3 more
wiley +1 more source
Materials Genome Engineering Advances, EarlyView.This study breaks extrapolation barriers in alloy design by merging symbolic regression with latent space sampling. The dual‐strategy framework enables accurate prediction of high‐hardness properties and navigates uncharted compositional spaces. The approach successfully designs novel high‐entropy alloys with hardness exceeding 863.5 HV, demonstrating ...
Zhigang Yu +6 more
wiley +1 more source
Implementation of a practical Markov chain Monte Carlo sampling algorithm in PyBioNetFit. [PDF]
Bioinformatics, 2022 Neumann J +8 more
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Mathematical Methods in the Applied Sciences, EarlyView.We develop a full randomization of the classical hyper‐logistic growth model by obtaining closed‐form expressions for relevant quantities of interest, such as the first probability density function of its solution, the time until a given fixed population is reached, and the population at the inflection point.
Juan Carlos Cortés +2 more
wiley +1 more source
Revista Colombiana de Estadística, 2011 In this paper, we introduce a Bayesian analysis for survival multivariate data in the presence of a covariate vector and censored observations. Different "frailties" or latent variables are considered to capture the correlation among the survival times ...
JORGE ALBERTO ACHCAR +1 more
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