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Showing 81 - 100 results of 178 for search '(( python code implementation ) OR ( python effective implementation ))', query time: 0.25s Refine Results
  1. 81
    BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories

    BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

    Published 2025
    “…We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”
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  2. 82
    BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories

    BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

    Published 2025
    “…We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”
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  3. 83
    BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories

    BaNDyT: Bayesian Network Modeling of Molecular Dynamics Trajectories by Elizaveta Mukhaleva (20602550)

    Published 2025
    “…We describe here the software’s uses, the methods associated with it, and a comprehensive Python interface to the underlying generalist BNM code. …”
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  4. 84
    High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch

    High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch by Andrey Samokhin (20282728)

    Published 2025
    “…Despite the availability of numerous library search algorithms, those developed by NIST and implemented in MS Search remain predominant, partly because commercial databases (e.g., NIST, Wiley) are distributed in proprietary formats inaccessible to custom code. …”
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  5. 85
    Comparison data 7 for <i>Lamprologus ocellatus</i>.

    Comparison data 7 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  6. 86
    Sample data for <i>Neolamprologus multifasciatus</i>.

    Sample data for <i>Neolamprologus multifasciatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  7. 87
    Sample data for <i>Lamprologus ocellatus</i>.

    Sample data for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  8. 88
    Comparison data 3 for <i>Lamprologus ocellatus</i>.

    Comparison data 3 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  9. 89
    Sample data for <i>Telmatochromis temporalis</i>.

    Sample data for <i>Telmatochromis temporalis</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  10. 90
    Comparison data 4 for <i>Lamprologus ocellatus</i>.

    Comparison data 4 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  11. 91
    Comparison data 1 for <i>Lamprologus ocellatus</i>.

    Comparison data 1 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  12. 92
    Comparison data 2 for <i>Lamprologus ocellatus</i>.

    Comparison data 2 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  13. 93
    Comparison data 5 for <i>Lamprologus ocellatus</i>.

    Comparison data 5 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  14. 94
    Comparison data 6 for <i>Lamprologus ocellatus</i>.

    Comparison data 6 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
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  15. 95
    Memory monitoring recognition test workflow.

    Memory monitoring recognition test workflow. by Pedro C. Martínez-Suárez (21192459)

    Published 2025
    “…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”
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  16. 96
    Voice recognition workflow.

    Voice recognition workflow. by Pedro C. Martínez-Suárez (21192459)

    Published 2025
    “…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”
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  17. 97
    Memory monitoring recognition test main screen.

    Memory monitoring recognition test main screen. by Pedro C. Martínez-Suárez (21192459)

    Published 2025
    “…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”
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  18. 98
    Task descriptions.

    Task descriptions. by Pedro C. Martínez-Suárez (21192459)

    Published 2025
    “…</p><p>Method</p><p>The MMRT was developed using Python and Kivy, facilitating the creation of cross-platform user interfaces. …”
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  19. 99
    Map of cumulative daily root-mean-square errors for each province in China in the test set.

    Map of cumulative daily root-mean-square errors for each province in China in the test set. by Xiaoyi Wang (90589)

    Published 2025
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  20. 100
    Summary of Tourism Dataset.

    Summary of Tourism Dataset. by Jing Zhang (23775)

    Published 2025
    “…The model employs robust forecasting of economic impacts, visitor spending patterns, and behavior while accounting for uncertainty through variational inference. The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …”
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