“…A Bayesian non-parametric (Dirichlet process) approach is used to cluster pathogen strain types by epidemiological behaviour, avoiding model overfitting and allowing detection of strain types associated with potentially high “virulence”. sourceR is demonstrated using Campylobacter jejuni isolate data collected in New Zealand between 2005 and 2008. …”
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“…Clusters on both the local and the global level are modelled using a hierarchical Dirichlet mixture model to identify structure on both levels. …”
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“…Laplace’s equation subject to Dirichlet-Neumann boundary conditions is adopted to construct the mapping between the virtual and physical spaces. …”
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“…The main idea of this algorithm is to calculate the unary potential, namely the initial label of the Dense CRF, by the unsupervised learning model LDA (Latent Dirichlet Allocation). In view of the ever-changing image features at different stages of fruit growth, a multi-resolution ULCRF is proposed to improve the accuracy of image segmentation in the middle stage and late stage of the fruit growth. …”
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“…Following previous works in this direction, we include a deviation parameter that has the effect of capturing the surplus, or deficit, in non-synonymous rates, relative to what would be expected under a mutation–selection modeling framework that includes a Dirichlet process approach to account for across-codon-site variation in amino acid fitness profiles. …”
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“…The proposed method enables a robot to form hierarchical spatial concepts by categorizing multimodal information using hierarchical multimodal latent Dirichlet allocation (hMLDA). Object recognition results using convolutional neural network (CNN), hierarchical k-means clustering result of self-position estimated by Monte Carlo localization (MCL), and a set of location names are used, respectively, as features in vision, position, and word information. …”
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“…The proposed Temporal Gaussian Process Model for Compositional Data Analysis (TGP-CODA) shows superior modeling performance compared to commonly used Dirichlet-multinomial, multinomial and non-parametric regression models on real and synthetic data. …”
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“…The key idea of this algorithm is to consider the relationship between the point sets as random variables and model the prior probabilities via Dirichlet distribution. We assign the various prior probabilities of each point to its correspondences in the Student’s-t mixture model. …”
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“…Despite their success—particularly of the most widely used variant called latent Dirichlet allocation (LDA)—and numerous applications in sociology, history, and linguistics, topic models are known to suffer from severe conceptual and practical problems, for example, a lack of justification for the Bayesian priors, discrepancies with statistical properties of real texts, and the inability to properly choose the number of topics. …”
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“…We try both a bivariate Normal as well as a Dirichlet Process Mixture Model, and compare the results via simulation. …”
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“…The current study proposes a new Bayesian phylogenetic clustering algorithm, which we refer to as DM-PhyClus (Dirichlet-Multinomial Phylogenetic Clustering), that identifies sets of sequences resulting from quick transmission chains, thus yielding easily-interpretable clusters, without using any ad hoc distance or confidence requirement. …”
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“…BACKGROUND: Bayesian clustering algorithms, in particular those utilizing Dirichlet Processes (DP), return a sample of the posterior distribution of partitions of a set. …”
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“…Specifically, we generated 50 topics based on diagnostic codes using latent Dirichlet allocation, and examined them for association with the risk variant. …”
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“…Using primate mandibular second molars, we investigated the effects of mesh preparation parameters smoothing, cropping, and triangle count/mesh resolution (herein, resolution) on six topographic variables (Dirichlet normal energy, DNE; orientation patch count rotated, OPCR; relief index, RFI; ambient occlusion, portion de ciel visible, PCV; enamel surface area, SA; tooth size) to determine the effects of smoothing, cropping, and triangle count/resolution on topographic values and the relationship between these values and diet. …”
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“…Texts were mined using the closed-vocabulary approach based on the Linguistic Inquiry Word Count (LIWC) semantic dictionary, and an open-vocabulary approach performed via Latent Dirichlet Allocation (LDA). Then, we examined associations between emerging textual features and alcohol-drinking scores as assessed using the AUDIT-C questionnaire. …”
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“…We used Python to extract the title, publication date, MeSH terms, and abstract from the metadata of each publication for bibliometric assessment. Latent Dirichlet allocation (LDA) was applied to the abstracts to identify publications' research topics with greater specificity. …”
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“…The hydra approach uses a Dirichlet process mixture model to automatically detect multimodally distributed genes and expression signatures without the need for matched normal tissue. …”
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“…METHODS: Based on the 10,861 depression questions collected in the Zhihu, the largest Q&A platform in China, we divided the healthy information needs description into nine categories with Latent Dirichlet Allocation (LDA). We also divided the healthy information needs type into Physiological, affective and cognitive needs based on the Wilson model. …”
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“…RESULTS: We propose a method called TopicNet that applies latent Dirichlet allocation to extract functional topics for a collection of genes regulated by a given TF. …”
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“…R and Python were used to extract publication date, MeSH terms and abstract from the metadata of each publication for bibliometric assessment. Latent Dirichlet allocation was applied to analyse the text from the articles’ abstracts to identify more specific research topics. …”
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