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Mostrando 121 - 140 Resultados de 1,151 Para Buscar '"dirichlet"', tiempo de consulta: 0.21s Limitar resultados
  1. 121
    “…Research topics were classified by latent Dirichlet allocation, and principal component analysis was used to identify the construct of the research landscape. …”
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    Modeling Research Topics for Artificial Intelligence Applications in Medicine: Latent Dirichlet Allocation Application Study
  2. 122
    “…RESULTS: We present MicroBVS, an R package for Dirichlet-tree multinomial models with Bayesian variable selection, for the identification of covariates associated with microbial taxa abundance data. …”
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    MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package
  3. 123
    “…In this article, we demonstrate that information specialists can support health and medical community by applying text mining technique with latent Dirichlet allocation procedure to perform an overview of a mass of coronavirus literature. …”
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    An overview of literature on COVID-19, MERS and SARS: Using text mining and latent Dirichlet allocation
  4. 124
    por Matsutani, Taro, Hamada, Michiaki
    Publicado 2020
    “…PLDA is an extended model of latent Dirichlet allocation (LDA), which is one of the methods used for signature prediction. …”
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    Parallelized Latent Dirichlet Allocation Provides a Novel Interpretability of Mutation Signatures in Cancer Genomes
  5. 125
    “…The Dirichlet Process (DP) mixture model has become a popular choice for model-based clustering, largely because it allows the number of clusters to be inferred. …”
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    Fast approximate inference for variable selection in Dirichlet process mixtures, with an application to pan-cancer proteomics
  6. 126
    “…RESULTS: Fecal microbiota was analyzed using 16S rRNA gene amplicon sequencing. Latent Dirichlet allocation (LDA) was applied to samples from 1992 participants to identify 20 microbial subgroups within the study population. …”
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    Associations between habitual diet, metabolic disease, and the gut microbiota using latent Dirichlet allocation
  7. 127
    “…This study aims to identify the motivating factors of urban forest visitors, using latent Dirichlet allocation (LDA) topic modeling based on social big data. …”
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    Determination of Motivating Factors of Urban Forest Visitors through Latent Dirichlet Allocation Topic Modeling
  8. 128
    “…The aim of this work is to solve the case study singular model involving the Neumann–Robin, Dirichlet, and Neumann boundary conditions using a novel computing framework that is based on the artificial neural network (ANN), global search genetic algorithm (GA), and local search sequential quadratic programming method (SQPM), i.e., ANN-GA-SQPM. …”
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    Artificial Neural Networks to Solve the Singular Model with Neumann–Robin, Dirichlet and Neumann Boundary Conditions
  9. 129
    “…The random walk part involves a combinatorial Dirichlet problem for a weighted graph, where the nodes are the pixel of the image, and the positive weights are related to the distances between pixels: in this work we propose a novel colour distance for computing such weights. …”
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    A Semiautomatic Multi-Label Color Image Segmentation Coupling Dirichlet Problem and Colour Distances
  10. 130
    “…A model with 31 latent Dirichlet allocation topics was best fitting, and 24 topics included posts that met our inclusion criteria for manual review. …”
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    Text mining of Reddit posts: Using latent Dirichlet allocation to identify common parenting issues
  11. 131
    “…The relative use of each OAC, as a fraction of all OACs prescribed, was analysed using Dirichlet regression to quantify the association between prescribing patterns and practice and area‐level characteristics. …”
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    Choice of oral anticoagulant prescribed by general practices in Wales: Application of Dirichlet regression and linked data
  12. 132
    “…We present a novel unsupervised deep learning approach called BindVAE, based on Dirichlet variational autoencoders, for jointly decoding multiple TF binding signals from open chromatin regions. …”
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    BindVAE: Dirichlet variational autoencoders for de novo motif discovery from accessible chromatin
  13. 133
    “…In the second part, unstructured predictor variables were extracted from the initial diagnosis made by physicians when the patients were admitted to the hospital and analyzed using Latent Dirichlet Allocation techniques. The structured and unstructured data were combined using machine learning methods to create a mortality risk prediction model for ICU patients. …”
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    Integrating Structured and Unstructured EHR Data for Predicting Mortality by Machine Learning and Latent Dirichlet Allocation Method
  14. 134
    por Ma, Ruijundi, Kim, Yong Jin
    Publicado 2023
    “…Then, based on latent dirichlet allocation (LDA) topic model, this study summarizes and confirms related words and meaning of each topic in different stages. …”
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    Tracing the evolution of green logistics: A latent dirichlet allocation based topic modeling technology and roadmapping
  15. 135
    “…In this paper, we present and compare four methods to enforce Dirichlet boundary conditions in Physics-Informed Neural Networks (PINNs) and Variational Physics-Informed Neural Networks (VPINNs). …”
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    Enforcing Dirichlet boundary conditions in physics-informed neural networks and variational physics-informed neural networks
  16. 136
    “…We propose a novel multivariate method to analyse biodiversity data based on the Latent Dirichlet Allocation (LDA) model. LDA, a probabilistic model, reduces assemblages to sets of distinct component communities. …”
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    Decomposing biodiversity data using the Latent Dirichlet Allocation model, a probabilistic multivariate statistical method
  17. 137
    por Chen, Yun, Yang, Hui
    Publicado 2016
    “…Further, we develop Dirichlet process (DP) models to cluster variables based on the mutual-information measures among variables. …”
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    A Novel Information-Theoretic Approach for Variable Clustering and Predictive Modeling Using Dirichlet Process Mixtures
  18. 138
    “…Introduction. The Dirichlet distribution has been proposed for representing preference heterogeneity, but there is limited evidence on its suitability for modeling population preferences on treatment benefits and risks. …”
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    From Individual to Population Preferences: Comparison of Discrete Choice and Dirichlet Models for Treatment Benefit-Risk Tradeoffs
  19. 139
    “…We performed the latent Dirichlet allocation (LDA) as a topic model using a Python library. …”
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    Topic Modeling of Social Networking Service Data on Occupational Accidents in Korea: Latent Dirichlet Allocation Analysis
  20. 140
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    Correction to: MicroBVS: Dirichlet-tree multinomial regression models with Bayesian variable selection - an R package
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