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Showing 1 - 20 results of 2,774 for search '(( elements method algorithm ) OR ((( data code algorithm ) OR ( based making algorithm ))))*', query time: 0.46s Refine Results
  1. 1
    Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40).

    Top-rated mode of transport based on the SEU algorithm (SEU scores from 0 to 40). by Johannes Weyer (13392175)

    Published 2025
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  2. 2
    Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets.

    Numbers of iterations (#Ite) and eigenvalue calculations (#Eig) in the DC algorithm on the random and chain graph datasets. by Tomokaze Shiratori (9635271)

    Published 2024
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  3. 3
    Performance of algorithms outside the training species.

    Performance of algorithms outside the training species. by Sven B. Gould (12237287)

    Published 2024
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  4. 4
    Source code.

    Source code. by Jesse Wheeler (18462457)

    Published 2025
    Subjects: “…routinely applicable algorithm…”
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  5. 5
    A framework for improving localisation prediction algorithms.

    A framework for improving localisation prediction algorithms. by Sven B. Gould (12237287)

    Published 2024
    “…Classifiers on which the algorithms are trained could include parameters such as the evolutionary distance of a species, non-coding regions, or a protein’s abundance as a currently neglected factor. …”
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  6. 6
    Computation time as a function of the sample size on the chain graph dataset.

    Computation time as a function of the sample size on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  7. 7
    Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges).

    Log-likelihood as a function of the number of selected edges on the chain graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

    Published 2024
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  8. 8
    Computation time as a function of the sample size on the random graph dataset.

    Computation time as a function of the sample size on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  9. 9
    F1 score of edges selected through cross-validation on the chain graph dataset.

    F1 score of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  10. 10
    Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges).

    Log-likelihood as a function of the number of selected edges on the random graph dataset (black dashed line: The true number of edges). by Tomokaze Shiratori (9635271)

    Published 2024
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  11. 11
    Examples of ground-truth graph structures with (<i>p</i>, <i>n</i><sub>≠0</sub>) = (10, 10).

    Examples of ground-truth graph structures with (<i>p</i>, <i>n</i><sub>≠0</sub>) = (10, 10). by Tomokaze Shiratori (9635271)

    Published 2024
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  12. 12
    Number of edges selected through cross-validation on the chain graph dataset.

    Number of edges selected through cross-validation on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  13. 13
    Number of edges selected through cross-validation on the random graph dataset.

    Number of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  14. 14
    Graphs of the regularization terms.

    Graphs of the regularization terms. by Tomokaze Shiratori (9635271)

    Published 2024
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  15. 15
    F1 score of a given number of selected edges on the chain graph dataset.

    F1 score of a given number of selected edges on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  16. 16
    Computation time as a function of the number of variables on the chain graph dataset.

    Computation time as a function of the number of variables on the chain graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  17. 17
    Computation time as a function of the number of variables on the random graph dataset.

    Computation time as a function of the number of variables on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  18. 18
    F1 score of a given number of selected edges on the random graph dataset.

    F1 score of a given number of selected edges on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  19. 19
    F1 score of edges selected through cross-validation on the random graph dataset.

    F1 score of edges selected through cross-validation on the random graph dataset. by Tomokaze Shiratori (9635271)

    Published 2024
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  20. 20
    Comparison of Uniform Manifold Approximation and Projection (UMAP)-based and feature-based spike sorting on synthetic data.

    Comparison of Uniform Manifold Approximation and Projection (UMAP)-based and feature-based spike sorting on synthetic data. by Daniel Suárez-Barrera (22676654)

    Published 2025
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