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Showing 1 - 20 results of 77 for search '(("element data algorithm") OR ((("_ maximization algorithm") OR ("neural coding algorithm"))))', query time: 0.29s Refine Results
  1. 1
    FIG. S2

    FIG. S2 by Bo Guo (1559695)

    Published 2025
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  2. 2
    FIG. S1

    FIG. S1 by Bo Guo (1559695)

    Published 2025
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  3. 3
    Simultaneous Estimation of Many Sparse Networks via Hierarchical Poisson Log-Normal Model

    Simultaneous Estimation of Many Sparse Networks via Hierarchical Poisson Log-Normal Model by Changhao Ge (22410399)

    Published 2025
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  4. 4
    Estimation error of candidate methods with a threshold of 0.05.

    Estimation error of candidate methods with a threshold of 0.05. by Lulu Pan (8977979)

    Published 2025
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  5. 5
    Estimation error of candidate methods with a threshold of 0.1.

    Estimation error of candidate methods with a threshold of 0.1. by Lulu Pan (8977979)

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  6. 6
    Estimation error of candidate methods with a threshold of 0.1, showing how estimation error varies with sample size.

    Estimation error of candidate methods with a threshold of 0.1, showing how estimation error varies with sample size. by Lulu Pan (8977979)

    Published 2025
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  7. 7
    Precision and recall (in parentheses) of candidate methods under different heterogeneity levels (<i>h</i> = 10 or 20), different numbers of transferable source datasets (), and different distributions of the error (<i>ε</i><sup>(<i>s</i>)</sup> follows normal distribution (N), <i>t</i>-distribution (t), contaminated normal distribution (CN), and skew <i>t</i>-distribution (St)).

    Precision and recall (in parentheses) of candidate methods under different heterogeneity levels (<i>h</i> = 10 or 20), different numbers of transferable source datasets (), and dif... by Lulu Pan (8977979)

    Published 2025
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  8. 8
    Relative prediction error of candidate methods relative to the PNLR with a threshold of 0.05.

    Relative prediction error of candidate methods relative to the PNLR with a threshold of 0.05. by Lulu Pan (8977979)

    Published 2025
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  9. 9
    Estimation error of candidate methods with a threshold of 0.1.

    Estimation error of candidate methods with a threshold of 0.1. by Lulu Pan (8977979)

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  10. 10
    File includes code "Transfer learning.R" and "updatebeta.cpp" for implementing transfer learning methods.

    File includes code "Transfer learning.R" and "updatebeta.cpp" for implementing transfer learning methods. by Lulu Pan (8977979)

    Published 2025
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  11. 11
    Relative prediction error of PtLR, Naive Trans-PNLR, Naive Trans-PtLR, Trans-PNLR, and Trans-PtLR relative to the PNLR.

    Relative prediction error of PtLR, Naive Trans-PNLR, Naive Trans-PtLR, Trans-PNLR, and Trans-PtLR relative to the PNLR. by Lulu Pan (8977979)

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  12. 12
    Relative prediction error of candidate methods relative to the PNLR with a threshold of 0.1.

    Relative prediction error of candidate methods relative to the PNLR with a threshold of 0.1. by Lulu Pan (8977979)

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  13. 13
    Distribution of error by normal linear regression for six tissues compared with normal distribution.

    Distribution of error by normal linear regression for six tissues compared with normal distribution. by Lulu Pan (8977979)

    Published 2025
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  14. 14
    Estimation error of candidate methods with a threshold of 0.15.

    Estimation error of candidate methods with a threshold of 0.15. by Lulu Pan (8977979)

    Published 2025
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  15. 15
    Relative prediction error of candidate methods relative to the PNLR with a threshold of 0.15.

    Relative prediction error of candidate methods relative to the PNLR with a threshold of 0.15. by Lulu Pan (8977979)

    Published 2025
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  16. 16
    Estimation error of candidate methods with a threshold of 0.1.

    Estimation error of candidate methods with a threshold of 0.1. by Lulu Pan (8977979)

    Published 2025
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  17. 17
    Comparison of recovered networks with the Gibbs sampler and the GEM algorithm using credible intervals.

    Comparison of recovered networks with the Gibbs sampler and the GEM algorithm using credible intervals. by Aapo E. Korhonen (22530674)

    Published 2025
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  18. 18
    The network recovered from the riboflavin dataset using the HMFGraph method.

    The network recovered from the riboflavin dataset using the HMFGraph method. by Aapo E. Korhonen (22530674)

    Published 2025
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  19. 19
    Model fit and imputation performance of BMDD.

    Model fit and imputation performance of BMDD. by Huijuan Zhou (5745020)

    Published 2025
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  20. 20
    Comparisons of median computation times (in seconds) based on 5 runs for the GEM algorithm and the MCMC methods.

    Comparisons of median computation times (in seconds) based on 5 runs for the GEM algorithm and the MCMC methods. by Aapo E. Korhonen (22530674)

    Published 2025
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