Showing 21 - 40 results of 1,994 for search '(( algorithm where function ) OR ( algorithm ((brain function) OR (python function)) ))', query time: 0.59s Refine Results
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    Heterogeneity Analysis on Multi-State Brain Functional Connectivity and Adolescent Neurocognition by Shiying Wang (5179559)

    Published 2024
    “…<p>Brain functional connectivity or connectome, a unique measure for brain functional organization, provides a great potential to explain the neurobiological underpinning of behavioral profiles. …”
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    EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit by Gonzalo Colmenarejo (650249)

    Published 2025
    “…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …”
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    The optimal solution set of NYN by using different algorithms. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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    The optimal solution set of HN by using different algorithms. by Yi Tao (178829)

    Published 2022
    Subjects: “…evolutionary genetic algorithm…”
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    Fig 3 - by Lulu Gong (18707874)

    Published 2024
    Subjects:
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    Data_Sheet_1_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

    Published 2020
    “…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”
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    Data_Sheet_2_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

    Published 2020
    “…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”
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    Data_Sheet_3_Multivariate Brain Functional Connectivity Through Regularized Estimators.DOCX by Raymond Salvador (813880)

    Published 2020
    “…On the one hand, simple linear functions of all brain nodes were fitted with ridge regression. …”
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    GraSPy: an Open Source Python Package for Statistical Connectomics by Benjamin Pedigo (6580352)

    Published 2019
    “…The package provides functionality for low-dimensional embeddings of graphs, statistical testing on individual or sets of graphs, simulations for several random graph models, as well as various plotting and utility functions for graph manipulation. …”
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