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driven optimization » design optimization (Expand Search), guided optimization (Expand Search), dose optimization (Expand Search)
all optimization » art optimization (Expand Search), ai optimization (Expand Search), whale optimization (Expand Search)
binary mapk » binary mask (Expand Search), binary image (Expand Search)
based all » based small (Expand Search), based cell (Expand Search), based ap (Expand Search)
lens » less (Expand Search)
Showing 1 - 12 results of 12 for search '(( binary mapk driven optimization algorithm ) OR ( lens based all optimization algorithm ))*', query time: 0.25s Refine Results
  1. 1
    S1 File -

    S1 File - by Michael Bonert (3751348)

    Published 2023
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  2. 2
    S2 File -

    S2 File - by Michael Bonert (3751348)

    Published 2023
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  3. 3
    Clinical history.

    Clinical history. by Michael Bonert (3751348)

    Published 2023
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  4. 4
    Neuroanatomical site overlap.

    Neuroanatomical site overlap. by Michael Bonert (3751348)

    Published 2023
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  5. 5
    Parameter settings.

    Parameter settings. by Yang Gao (18005)

    Published 2025
    “…The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …”
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  6. 6
    Fusion framework.

    Fusion framework. by Yang Gao (18005)

    Published 2025
    “…The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …”
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  7. 7
    Generation steps of user profiles.

    Generation steps of user profiles. by Yang Gao (18005)

    Published 2025
    “…The study proposes a movie recommendation algorithm framework that integrates Knowledge Graph Embedding via Dynamic Mapping Matrix (TransD) and Artificial Intelligence Generated Content (AIGC)-based generative semantic modeling. …”
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  8. 8
    Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty

    Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty by Ki-Tae Kim (10184066)

    Published 2021
    “…The central questions are: How do we optimally learn from data through the lens of models? …”
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  9. 9
    SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion

    SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion by Omar Ghattas (4387300)

    Published 2020
    “…The central questions are: How do we optimally learn from data through the lens of models? …”
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  10. 10
    SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion

    SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion by Umberto Villa (8400192)

    Published 2020
    “…The central questions are: How do we optimally learn from data through the lens of models? …”
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  11. 11
    Massive Mixed Models in Julia

    Massive Mixed Models in Julia by Phillip M. Alday (2814652)

    Published 2025
    “…<br><br>Although we are already very excited to be able to fit such large models at all, we want to fit them even faster. Julia enables us to continue algorithmic development in a coherent way. …”
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  12. 12
    <b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043)

    <b>AI for imaging plant stress in invasive species </b>(dataset from the article https://doi.org/10.1093/aob/mcaf043) by Erola Fenollosa (20977421)

    Published 2025
    “…</li><li>The dataframe of extracted colour features from all leaf images and lab variables (ecophysiological predictors and variables to be predicted)</li><li>Set of scripts used for image pre-processing, features extraction, data analytsis, visualization and Machine learning algorithms training, using ImageJ, R and Python.…”
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