Data integration for multiple alkali metals in predicting coordination energies based on Bayesian inference by Koki Obinata, Tomofumi Nakayama, Atsushi Ishikawa, Keitaro Sodeyama, Kenji Nagata, Yasuhiko Igarashi, Masato Okada

“…We evaluate the confidence level of feature selection by calculating the posterior probabilities of features using Bayesian model averaging (BMA). …”
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Two New Edible <i>Lyophyllum</i> Species from Tibetan Areas, China by Shuhong Li, Songming Tang, Jun He, Dequn Zhou

“…In the phylogenetic analyses, our two new species formed distinct clades that are well supported by posterior probabilities and bootstrap proportions. Detailed descriptions, colour photos, illustrations and a phylogenetic tree to show the positions of the two new species are presented.…”
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Combining epidemiologic and biostatistical tools to enhance variable selection in HIV cohort analyses. by Christopher Rentsch, Ionut Bebu, Jodie L Guest, David Rimland, Brian K Agan, Vincent Marconi

“…When comparing the parsimonious model to the previously published model, there was evidence of less variance in the main survival estimates.The variable selection approaches considered in this study allowed building a model based on significance tests, on an information criterion, and on averaging models using their posterior probabilities. A parsimonious model that balanced these three approaches was found to provide a better fit than the previously reported model.…”
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A Data-Driven Kernel Principal Component Analysis–Bagging–Gaussian Mixture Regression Framework for Pulverizer Soft Sensors Using Reduced Dimensions and Ensemble Learning by Shengxiang Jin, Fengqi Si, Yunshan Dong, Shaojun Ren

“…Ultimately, the fusion output is achieved by calculating the weights of each local model based on Bayesian posterior probabilities. By conducting simulation experiments on the coal mill, the proposed approach has been validated as demonstrating superior predictive accuracy and excellent generalization capabilities.…”
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Inverse Modeling of Hydrologic Parameters in CLM4 via Generalized Polynomial Chaos in the Bayesian Framework by Georgios Karagiannis, Zhangshuan Hou, Maoyi Huang, Guang Lin

“…Our approach accounts for bases selection uncertainty and quantifies the importance of the gPC terms, and, hence, all of the input parameters, via the associated posterior probabilities.…”
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A Joint Land Cover Mapping and Image Registration Algorithm Based on a Markov Random Field Model by Apisit Eiumnoh, Preesan Rakwatin, Ratchawit Sirisommai, Teerasit Kasetkasem

“…The expectation maximization (EM) algorithm is employed to solve the joint image classification and registration problem by iteratively estimating the map parameters and approximate posterior probabilities. Then, the maximum a posteriori (MAP) criterion is used to produce an optimum land cover map. …”
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Diversification of the shell shape and size in Baikal Candonidae ostracods inferred from molecular phylogeny by Ivana Karanovic, Huyen T. M. Pham, Tatiana Sitnikova

“…We reconstruct their molecular phylogeny with 46 species and two markers (18S and 16S rRNA), and use it to estimate the evolution of the shell shape and size with landmark-based geometric morphometrics (LBGM). High posterior probabilities support four major clades, which differ in node depth and morphospace clustering. …”
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A Comparative Study on Recent Automatic Data Fusion Methods by Luis Manuel Pereira, Addisson Salazar, Luis Vergara

“…Late fusion has two setups, combination of the posterior probabilities (scores), which is called soft fusion, and combination of the decisions, which is called hard fusion. …”
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Waveform Design for Multi-Target Detection Based on Two-Stage Information Criterion by Yu Xiao, Xiaoxiang Hu

“…In the second stage, the objective function is designed based on the criterion of MI minimization and Kullback–Leibler divergence (KLD) maximization between multi-hypothesis posterior probabilities, and the waveform is chosen from the waveform library of the first-stage parameter estimation. …”
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A Fast and Accurate Guessing Entropy Estimation Algorithm for Full-key Recovery by Ziyue Zhang, A. Adam Ding, Yunsi Fei

“…A recent estimation method based on posterior probabilities, although scalable, is not accurate. …”
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Properties of neurons in external globus pallidus can support optimal action selection by Bogacz, R, Martin Moraud, E, Abdi, A, Magill, P, Baufreton, J

“…We conclude that, by virtue of their distinct response properties and connectivities, a network of arkypallidal and prototypic GPe neurons comprises a neural substrate capable of supporting the computation of the posterior probabilities of actions.…”

Vascular segmentation of phase contrast magnetic resonance angiograms based on statistical mixture modeling and local phase coherence. by Chung, A, Noble, J, Summers, P

“…A statistical measure from the speed images and the LPC measure from the phase images are combined in a probabilistic framework, based on the maximum a posteriori method and Markov random fields, to estimate the posterior probabilities of vessel and background for classification. …”

<i>ImbTreeEntropy</i> and <i>ImbTreeAUC</i>: Novel R Packages for Decision Tree Learning on the Imbalanced Datasets by Krzysztof Gajowniczek, Tomasz Ząbkowski

“…Both applications enable optimization of the thresholds where posterior probabilities determine final class labels in a way that misclassification costs are minimized. …”
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Anomaly Detection in Gas Turbine Fuel Systems Using a Sequential Symbolic Method by Fei Li, Hongzhi Wang, Guowen Zhou, Daren Yu, Jiangzhong Li, Hong Gao

“…A structural Finite State Machine is used to evaluate posterior probabilities of observing symbolic sequences and the most probable state sequences they may locate. …”
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A Diagnosability-Integrated Design Approach Based on Graph Theory by Jiapeng Lv, Xianjun Shi

“…Finally, a cascade classifier was set on the maximal clique set to classify and identify faults in the system, and the performance of the diagnosis scheme was evaluated using the posterior probabilities of the classifier outputs combined with the Shannon entropy. …”
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An Efficient Application of Turbo Coding for OFDM In-Phase/Quadrature Index Modulation by Eunchul Yoon, Soonbum Kwon, Sun Yong Kim

“…We show that using the posterior probabilities of turbo-coded bits in the Bahl-Cocke-Jelinek-Raviv (BCJR) decoding algorithm yields the same decoding performance as using the likelihood probabilities of turbo-coded bits. …”
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Introduction of two novel species of Hymenopellis (Agaricales, Physalacriaceae) from Thailand by Allen Grace T. Niego, Naritsada Thongklang, Kevin D. Hyde, Olivier Raspé

“…In the inferred phylogenies, the new species from this study formed distinct clades well supported by bootstrap proportions and posterior probabilities. The studied specimen affine to H. orientalis produced 2-spored basidia whereas published descriptions of other specimens mention 4-spored basidia. …”
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Fine mapping spatiotemporal mechanisms of genetic variants underlying cardiac traits and disease by Matteo D’Antonio, Jennifer P. Nguyen, Timothy D. Arthur, iPSCORE Consortium, Hiroko Matsui, Agnieszka D’Antonio-Chronowska, Kelly A. Frazer

“…Colocalization between eQTL and GWAS signals of five cardiac traits identified variants with high posterior probabilities for being causal in 210 GWAS loci. …”
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Inferring adversarial behaviour in cyber‐physical power systems using a Bayesian attack graph approach by Abhijeet Sahu, Katherine Davis

“…Then, Bayes‐CAPS computes the posterior probabilities of the occurrence of a security breach event in power systems. …”
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Resources allocation optimization algorithm based on the comprehensive utility in edge computing applications by Yanpei Liu, Yunjing Zhu, Yanru Bin, Ningning Chen

“…First, the algorithm improves the Naive Bayes algorithm, obtains the conditional probabilities of job types based on the established Naive Bayes formula and calculates the posterior probabilities of different job types under specific conditions. …”
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