Results 11 to 20 of about 15,712,923 (297)
A sensorimotor paradigm for Bayesian model selection [PDF]
Frontiers in Human Neuroscience, 2012 Sensorimotor control is thought to rely on predictive internal models in order to cope efficientlywith uncertain environments. Recently, it has been shown that humans not only learn differentinternal models for different tasks, but that they also extract
Tim eGenewein +3 more
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Bayesian Computation and Model Selection Without Likelihoods [PDF]
Genetics, 2010 AbstractUntil recently, the use of Bayesian inference was limited to a few cases because for many realistic probability models the likelihood function cannot be calculated analytically. The situation changed with the advent of likelihood-free inference algorithms, often subsumed under the term approximate Bayesian computation (ABC).
Leuenberger, Christoph, Wegmann, Daniel
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Prior elicitation and variable selection for bayesian quantile regression [PDF]
, 2013 This thesis was submitted for the degree of Doctor of Philosophy and awarded by Brunel University.Bayesian subset selection suffers from three important difficulties: assigning priors over model space, assigning priors to all components of the regression
Al-Hamzawi, Rahim Jabbar Thaher
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Bayesian outcome selection modeling
Stat, 2023 In psychiatric and social epidemiology studies, it is common to measure multiple different outcomes using a comprehensive battery of tests thought to be related to an underlying construct of interest. In the research that motivates our work, researchers wanted to assess the impact of in utero alcohol exposure on child cognition and neuropsychological ...
Khue‐Dung Dang +5 more
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Bayesian evidence and model selection [PDF]
Digital Signal Processing, 2015 Arxiv version consists of 58 pages and 9 figures.
Kevin H. Knuth +4 more
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BMC Bioinformatics, 2023 Background Genome-wide association studies (GWAS) seek to identify single nucleotide polymorphisms (SNPs) that cause observed phenotypes. However, with highly correlated SNPs, correlated observations, and the number of SNPs being two orders of magnitude ...
Jacob Williams +2 more
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Active Knowledge Extraction from Cyclic Voltammetry
Energies, 2022 Cyclic Voltammetry (CV) is an electro-chemical characterization technique used in an initial material screening for desired properties and to extract information about electro-chemical reactions.
Kiran Vaddi, Olga Wodo
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Model Selection for Bayesian Autoencoders
CoRR, 2021 We develop a novel method for carrying out model selection for Bayesian autoencoders (BAEs) by means of prior hyper-parameter optimization. Inspired by the common practice of type-II maximum likelihood optimization and its equivalence to Kullback-Leibler divergence minimization, we propose to optimize the distributional sliced-Wasserstein distance ...
Ba-Hien Tran +5 more
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Feature Selection Based on Sparse Bayesian Model [PDF]
Jisuanji gongcheng, 2017 Through using sparse Bayesian inference thought,a Feature Selection Probabilistic Classification Vector Machine (FPCVM) is designed which can learn optimal classifier and automatically select the most relevant feature subset.FPCVM is an extension of ...
ZHU Pu,HUANG Zhangjin
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Radiometric Scale Transfer Using Bayesian Model Selection
Proceedings, 2020 The key input quantity to climate modelling and weather forecasts is the solar beam irradiance, i.e., the primary amount of energy provided by the sun.
Donald W. Nelson, Udo von Toussaint
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