Results 11 to 20 of about 157,395 (292)
Post hoc Bayesian model selection
NeuroImage, 2011 This note describes a Bayesian model selection or optimization procedure for post hoc inferences about reduced versions of a full model. The scheme provides the evidence (marginal likelihood) for any reduced model as a function of the posterior density over the parameters of the full model.
Karl J Friston, Will Penny
exaly +4 more sources
Detection of arterial wall abnormalities via Bayesian model selection [PDF]
Royal Society Open Science, 2019 Patient-specific modelling of haemodynamics in arterial networks has so far relied on parameter estimation for inexpensive or small-scale models.
Karen Larson +4 more
doaj +2 more sources
Bayesian feature and model selection for Gaussian mixture models [PDF]
IEEE Transactions on Pattern Analysis and Machine Intelligence, 2006 We present a Bayesian method for mixture model training that simultaneously treats the feature selection and the model selection problem. The method is based on the integration of a mixture model formulation that takes into account the saliency of the features and a Bayesian approach to mixture learning that can be used to estimate the number of ...
Constantinos Constantinopoulos +1 more
exaly +4 more sources
Spatially-dependent Bayesian model selection for disease mapping. [PDF]
Stat Methods Med Res, 2018 In disease mapping where predictor effects are to be modeled, it is often the case that sets of predictors are fixed, and the aim is to choose between fixed model sets.
Carroll R +5 more
europepmc +3 more sources
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
openaire +5 more sources
Bayesian evidence and model selection [PDF]
Digital Signal Processing, 2015 Arxiv version consists of 58 pages and 9 figures.
Kevin H. Knuth +4 more
openaire +4 more sources
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
openaire +3 more sources
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
doaj +1 more source
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
doaj +1 more source
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
doaj +1 more source