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Showing 321 - 340 results of 1,666 for search '(( element method algorithm ) OR ((( data code algorithm ) OR ( based approximation algorithm ))))', query time: 0.53s Refine Results
  1. 321
    Data Sheet 1_Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model.docx

    Data Sheet 1_Fast forward modeling and response analysis of extra-deep azimuthal resistivity measurements in complex model.docx by Pan Zhang (206408)

    Published 2025
    “…Considering the increased detection range of EDARM and the requirements for computational efficiency, this paper presents a 2.5-dimensional (2.5D) finite element method (FEM). By leveraging the symmetry of simulated signals in the spectral domain, the algorithm reduces computation time by 50%, significantly enhancing computational efficiency while preserving accuracy. …”
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  2. 322
    Genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA.

    Genes of the epistastic interactions detected on the seven GWAS data using Epi-SSA. by Liyan Sun (760586)

    Published 2024
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  3. 323
    <b>The Negative Digital Root Implemented as a Mathematica Standalone Function</b>

    <b>The Negative Digital Root Implemented as a Mathematica Standalone Function</b> by Paul F. Marrero Romero (17450601)

    Published 2024
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  4. 324
    The code for sample size calculation.

    The code for sample size calculation. by Ying Zhou (25031)

    Published 2025
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  5. 325
    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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  6. 326
    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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  7. 327
    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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  8. 328
    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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  9. 329
    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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  10. 330
    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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  11. 331
    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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  12. 332
    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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  13. 333
    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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  14. 334
    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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  15. 335
    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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  16. 336
    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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  17. 337
    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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  18. 338
    Two comparative performance measures for the three methods Troika, Combo, and Gurobi IP on the ABR benchmark dataset: (a) Extent of sub-optimality, (b) solve time.

    Two comparative performance measures for the three methods Troika, Combo, and Gurobi IP on the ABR benchmark dataset: (a) Extent of sub-optimality, (b) solve time. by Samin Aref (22226678)

    Published 2025
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  19. 339
    Two comparative performance measures for the three methods Troika, Combo, and Gurobi IP on the clusedit benchmark dataset: (a) Extent of sub-optimality, (b) solve time.

    Two comparative performance measures for the three methods Troika, Combo, and Gurobi IP on the clusedit benchmark dataset: (a) Extent of sub-optimality, (b) solve time. by Samin Aref (22226678)

    Published 2025
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  20. 340
    The respective partitions returned by Troika for the networks of S&P 500 market index from 2000 to 2024.

    The respective partitions returned by Troika for the networks of S&P 500 market index from 2000 to 2024. by Samin Aref (22226678)

    Published 2025
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