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Showing 1 - 20 results of 5,055 for search '(( algorithm body function ) OR ((( algorithm wave function ) OR ( algorithm b function ))))', query time: 1.10s Refine Results
  1. 1
    A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases

    A Genetic Algorithm Approach for Compact Wave Function Representations in Spin-Adapted Bases by Maru Song (22593561)

    Published 2025
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  2. 2
    The SSIM for the different algorithms.

    The SSIM for the different algorithms. by Bingbing Li (461702)

    Published 2024
    “…Different types of noise require different denoising algorithms and techniques to maintain image quality and fidelity. …”
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  3. 3
    Ridge wave transformation flowchart.

    Ridge wave transformation flowchart. by Bingbing Li (461702)

    Published 2024
    “…Different types of noise require different denoising algorithms and techniques to maintain image quality and fidelity. …”
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  4. 4
    Block ridge wave denoising flowchart.

    Block ridge wave denoising flowchart. by Bingbing Li (461702)

    Published 2024
    “…Different types of noise require different denoising algorithms and techniques to maintain image quality and fidelity. …”
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  5. 5
    The training process for PV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs.

    The training process for PV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

    Published 2025
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  6. 6
    The training process for AV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs.

    The training process for AV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

    Published 2025
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  7. 7
    The training process for TV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs.

    The training process for TV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

    Published 2025
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  8. 8
    The training process for MV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs.

    The training process for MV data. (a) Training accuracy as a function of epochs. (b) Training loss as a function of epochs. by Hiam Alquran (17636906)

    Published 2025
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  9. 9
    Greedy optimization algorithm.

    Greedy optimization algorithm. by Alexis Bénichou (19832361)

    Published 2024
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  10. 10
    Patient-reported function, pain interference, mood, and sleep vary by cluster membership.

    Patient-reported function, pain interference, mood, and sleep vary by cluster membership. by Benedict J. Alter (9745466)

    Published 2021
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  11. 11
    The optimal contact/quarantine rates from the family of functions (4) and (5) for Hainan and Xinjiang.

    The optimal contact/quarantine rates from the family of functions (4) and (5) for Hainan and Xinjiang. by Mengqi He (5753525)

    Published 2023
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  12. 12
    The details of the Scelestial algorithm.

    The details of the Scelestial algorithm. by Mohammad-Hadi Foroughmand-Araabi (6658772)

    Published 2022
    “…<p>The inputs to the Scelestial algorithm are a) a set of sequences <i>S</i>, b) the degree of restriction of the restricted Steiner tree <i>k</i>. …”
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  13. 13
    Data fitting and inference of the time-dependent parameters by TDINN algorithm for multiple waves of COVID-19 infection in Liaoning province.

    Data fitting and inference of the time-dependent parameters by TDINN algorithm for multiple waves of COVID-19 infection in Liaoning province. by Mengqi He (5753525)

    Published 2023
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  14. 14
    The optimal contact/quarantine rates from the family of functions (4) and (5) for Xi’an, Guangzhou and Yangzhou.

    The optimal contact/quarantine rates from the family of functions (4) and (5) for Xi’an, Guangzhou and Yangzhou. by Mengqi He (5753525)

    Published 2023
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  15. 15
    Excited-State DMRG Made Simple with FEAST

    Excited-State DMRG Made Simple with FEAST by Alberto Baiardi (1914601)

    Published 2021
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  16. 16
    Excited-State DMRG Made Simple with FEAST

    Excited-State DMRG Made Simple with FEAST by Alberto Baiardi (1914601)

    Published 2021
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  17. 17
    Multiresolution Spectro-Temporal Sound Analysis (MRSTSA) algorithm.

    Multiresolution Spectro-Temporal Sound Analysis (MRSTSA) algorithm. by Dario Dematties (6812390)

    Published 2019
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  18. 18
    Relationship between cardiac output (CO) measured with transthoracic Doppler echocardiography (TTE) and estimated with the Antares oscillometric pulse wave analysis algorithm in patients with cardiovascular diseases (n = 59).

    Relationship between cardiac output (CO) measured with transthoracic Doppler echocardiography (TTE) and estimated with the Antares oscillometric pulse wave analysis algorithm in pa... by Alexander Stäuber (10353580)

    Published 2024
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  19. 19
    Test on the remeshing algorithm with <i>N</i> = 50 points.

    Test on the remeshing algorithm with <i>N</i> = 50 points. by Ondrej Maxian (8722185)

    Published 2020
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  20. 20
    Relationship between cardiac output (CO) measured with transthoracic Doppler echocardiography (TTE) and estimated with the Antares oscillometric pulse wave analysis algorithm in male patients with cardiovascular diseases (n = 45).

    Relationship between cardiac output (CO) measured with transthoracic Doppler echocardiography (TTE) and estimated with the Antares oscillometric pulse wave analysis algorithm in ma... by Alexander Stäuber (10353580)

    Published 2024
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