“…Skip-chain models are capable of capturing, long distant and the time-delayed regulations. Use of a Dirichlet prior over parameters and Gibbs prior over structure can greatly reduce the over-fitting in the new model.…”
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“…The key idea lies in the development of a Dirichlet process (DP) prior distribution, called Bayesian experts, which reflects substantive knowledge on reaction mechanisms inherent in given models and experimentally observable kinetic evidences to the subsequent parameter search. …”
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“…In this method, we use a Dirichlet process prior for the distribution of SNP-specific regression coefficients, conduct hierarchical clustering with a distance measure derived from posterior pairwise probabilities of two SNPs having the same regression coefficient, and explore data-driven approaches to select the number of clusters. …”
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“…Scoring is achieved using the Bayesian-Dirichlet Equivalent method and significance is assessed by randomization via bootstrapping of the columns of the input matrix. …”
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“…Then, we employ a probabilistic topic model -- the Latent Dirichlet Allocation (LDA) model to the reads, which generates a number of hidden "topics" such that each read can be represented by a distribution vector of the generated topics. …”
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“…Unlike previous studies, a reactive Robin boundary condition (BC), rather than the absolute absorbing (Dirichlet) BC, is considered on the reactive boundaries. …”
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“…Grade of membership models, also known as “admixture models”, “topic models” or “Latent Dirichlet Allocation”, are a generalization of cluster models that allow each sample to have membership in multiple clusters. …”
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“…We take advantage of both Latent Dirichlet Allocation (LDA) modeling and network-based analysis for their capabilities of detecting latent associations and reducing noises for large volume data respectively. …”
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“…In 3VSR the theoretical capabilities are based on Dirichlet distribution by considering prior and posterior uncertainty of the said event. …”
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“…To provide a comprehensive content analysis of ES research literature, we employ a latent Dirichlet allocation algorithm. For three different time periods (1990–2000, 2001–2010, 2011–2016), we derive nine main ES topics arising from content analysis and elaborate on how they are related over time. …”
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“…Most existing approaches either add a small number called a pseudo-count or use probability models such as the multinomial and Dirichlet-multinomial distributions to explain the excess zero counts, which may produce unnecessary biases and impose a correlation structure taht is unsuitable for microbiome data. …”
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“…The proper boundary conditions were nonstandard, either mixed Dirichlet–Neumann or partial-flux. In addition, the model implies imperfect or hindered bud formation as well as nearly equal distances between buds. …”
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“…We demonstrate our method on a prototype model of N attractive cold bosons contained in a one-dimensional box with Dirichlet boundary conditions. Although we limit ourselves to a truncated system, we observe a rich structure of quantum phases with a critical point of enhanced memory capacity.…”
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“…RESULTS: This article contributes spatial-Dirichlet Gaussian mixture model (DGMM), an algorithm and a workflow for the analyses of MSI experiments, that detects components of single-ion images with homogeneous spatial composition. …”
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“…In this study, we used Latent Dirichlet Allocation (LDA), a generative model, to identify topics and determine their trends (i.e., cold and hot topics) by analyzing the abstracts of 19,000 publications from the Web of Science that were related to diatoms during 1991–2018. …”
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“…Analyses based on the different levels of data and methods using using VOSviewer software tool (version 1.16.15, Centre for Science and Technology Studies (CWTS), Leiden University, Leiden, The Netherlands) and Latent Dirichlet allocation. By exploring the trends in research productivity and topics, an increase was found in the number of papers mentioning non-pharmacological interventions as well as mental health illness and QoL among patients with COPD. …”
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“…Next, a text analysis was performed on the posts’ contents using a combination of latent Dirichlet allocation (LDA), sentiment analysis, and correlation analysis. …”
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“…This non-uniform distribution of blocks for [Formula: see text] contrasts Dirichlet’s theorem that guarantees equiprobability for [Formula: see text]. …”
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“…Natural Language Processing (NLP) using sentiment analysis and Latent Dirichlet Allocation (LDA) approach was applied to analyze the semi-structured survey data collected from 72 respondents. …”
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“…METHODS: In order to map these patterns, online depression forums are analyzed with natural language processing methods, where computational tools are complemented with a qualitative approach. Latent Dirichlet Allocation topic model of depression-related posts from the most popular English-speaking online health discussion forums (N = ~70 000) reveals the monolog (attributions and self-disclosures) and interactive (consultations and quasi-therapeutic interactions) patterns. …”
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