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Showing 21 - 40 results of 1,152 for search '(( python tool implementation ) OR ( ((python model) OR (python code)) predictive ))', query time: 0.47s Refine Results
  1. 21
    IJGIS-2020-0089_dataset&codes

    IJGIS-2020-0089_dataset&codes by zhewei liu (7519670)

    Published 2020
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  2. 22
    NLoed: A Python Package for Nonlinear Optimal Experimental Design in Systems Biology

    NLoed: A Python Package for Nonlinear Optimal Experimental Design in Systems Biology by Nathan Braniff (14149834)

    Published 2022
    “…To support OED investigations, the NLoed package implements maximum likelihood fitting and diagnostic tools, providing a comprehensive modeling workflow. …”
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  3. 23
    Numbers of predictions.

    Numbers of predictions. by Bjørn André Bredesen-Aa (13767126)

    Published 2022
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  4. 24
    python3 software to reproduce Figs 6, 7 and 8.

    python3 software to reproduce Figs 6, 7 and 8. by Stéphane Plaszczynski (14992817)

    Published 2023
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  5. 25
    Functions 1.0

    Functions 1.0 by Jonatan Flyckt (8101010)

    Published 2023
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  6. 26
    Functions 2.0

    Functions 2.0 by Jonatan Flyckt (8101010)

    Published 2023
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  7. 27
    Prediction overlap with experimental data.

    Prediction overlap with experimental data. by Bjørn André Bredesen-Aa (13767126)

    Published 2022
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  8. 28
    The maximum deviation of SDR with different <i>c</i>-values predict by ITC measurement model and variance function.

    The maximum deviation of SDR with different <i>c</i>-values predict by ITC measurement model and variance function. by Xiujie Ge (6831833)

    Published 2020
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  9. 29
    +5 Million Python & Bash Programming Submissions for 5 Courses & Grades for Computer-Based Exams over 3 academic years.

    +5 Million Python & Bash Programming Submissions for 5 Courses & Grades for Computer-Based Exams over 3 academic years. by David Azcona (9085694)

    Published 2020
    “…In this work we explore different mechanisms to represent students’ code to predict its correctness and to better analyze students’ progress using their interactions which can be exploited to provide effective feedback and support better recommendations. …”
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  10. 30
    Model for the maximal effective bandwidth of numerical models (lines = model prediction by Eq 12; symbols = measured maximal effective bandwidth; filled = f64; hollow = f32; black = CPU medium; red = CPU large; blue = GPU medium; magenta = GPU large).

    Model for the maximal effective bandwidth of numerical models (lines = model prediction by Eq 12; symbols = measured maximal effective bandwidth; filled = f64; hollow = f32; black... by Xuzhen He (14676114)

    Published 2023
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  11. 31
    Predictions at the A) <i>invected</i> and B) <i>vestigial</i> loci.

    Predictions at the A) <i>invected</i> and B) <i>vestigial</i> loci. by Bjørn André Bredesen-Aa (13767126)

    Published 2022
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  12. 32
    Appendices (Supplementary material).docx

    Appendices (Supplementary material).docx by Seyed Iman Mohammadpour (14783125)

    Published 2023
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  13. 33
    Code program.

    Code program. by Honglei Pang (22693724)

    Published 2025
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  14. 34
    Table_1_BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts.xlsx

    Table_1_BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts.xlsx by Kirill Batmanov (3722374)

    Published 2019
    “…BayesPI-BAR2 is a useful tool for predicting functional non-coding mutations in whole genome sequencing data: it allows identification of novel transcription factors (TFs) whose binding is altered by non-coding mutations in cancer. …”
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  15. 35
    Table_2_BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts.docx

    Table_2_BayesPI-BAR2: A New Python Package for Predicting Functional Non-coding Mutations in Cancer Patient Cohorts.docx by Kirill Batmanov (3722374)

    Published 2019
    “…BayesPI-BAR2 is a useful tool for predicting functional non-coding mutations in whole genome sequencing data: it allows identification of novel transcription factors (TFs) whose binding is altered by non-coding mutations in cancer. …”
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  16. 36
    Model for the effective bandwidth of element-wise operations (lines = model prediction by Eq 11; symbols = measured maximal effective bandwidth; filled symbols = matrix operations; hollow symbols = vector operations; circles = CPU; triangles = GPU; black = medium f64; red = medium f32; blue = large f64; magenta = large f32).

    Model for the effective bandwidth of element-wise operations (lines = model prediction by Eq 11; symbols = measured maximal effective bandwidth; filled symbols = matrix operations;... by Xuzhen He (14676114)

    Published 2023
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  17. 37
    Tools used in implementing the RNN models.

    Tools used in implementing the RNN models. by Fahmi H. Quradaa (17896527)

    Published 2024
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  18. 38
    One-hot coding map.

    One-hot coding map. by Zhengqiao Zhao (6400832)

    Published 2021
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  19. 39
    Five Operator Lattice Simulation

    Five Operator Lattice Simulation by James McDaniel (22522571)

    Published 2025
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  20. 40
    Multiprocessing and GPU application of SVMs significantly reduces run-times.

    Multiprocessing and GPU application of SVMs significantly reduces run-times. by Bjørn André Bredesen-Aa (13767126)

    Published 2022
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