يعرض 101 - 120 نتائج من 179 نتيجة بحث عن '((python models) OR (python code)) represented', وقت الاستعلام: 0.20s تنقيح النتائج
  1. 101

    Dataset for CNN-based Bayesian Calibration of TELEMAC-2D Hydraulic Model حسب Jose Zevallos (21379988)

    منشور في 2025
    "…</li></ul></li></ul><p dir="ltr">The <code>.npy</code> files were loaded and processed using the following approach in Python:</p><p dir="ltr"># Load the input and output numpy arrays</p><p dir="ltr">input_path = "..…"
  2. 102
  3. 103

    Data Sheet 1_Establishing a real-time biomarker-to-LLM interface: a modular pipeline for HRV signal acquisition, processing, and physiological state interpretation via generative A... حسب Morris Gellisch (18627744)

    منشور في 2025
    "…</p>Discussion<p>This system represents an early prototype of bioadaptive AI, in which physiological signals are incorporated as part of the model's input context.…"
  4. 104

    LGF v7HELLAS: A Dynamical Model of Ethical Convergence and Lambda-Zero Transition حسب heojeongbeom heo (22544705)

    منشور في 2025
    "…<h2><b>Description</b></h2><p dir="ltr"><b>LGF v7.Hellas</b> represents the final, validated form of the <i>Language Gravitational Field (LGF)</i> model, completing the transition from early unstable versions (v5.2) to the fully stable, reproducible, scientifically grounded system (v5.3 → v7.0 → v7.Hellas).…"
  5. 105
  6. 106

    Exploring post-wildfire hydrologic response in central Colorado using field observations and the Landlab modeling framework حسب Jordan Adams (595056)

    منشور في 2024
    "…Landlab, an open-source, componentized model written in Python, can be used to explore landscape evolution across both short and long time scales. …"
  7. 107

    Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx حسب Piyachat Udomwong (22563212)

    منشور في 2025
    "…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…"
  8. 108

    Oka et al., Supplementary Data for "Development of a battery emulator using deep learning model to predict the charge–discharge voltage profile of lithium-ion batteries" حسب Kanato Oka (20132185)

    منشور في 2024
    "…(<b>DOI:</b> 10.1038/s41598-024-80371-9 )<br><br>A zip file contains following data and codes.</p><p dir="ltr"><br></p><p dir="ltr">01_lstm_model_making.py</p><p dir="ltr">This file is a Python script for reading battery charge-discharge data and training an LSTM model. …"
  9. 109

    Smart Reaction Templating: A Graph-Based Method for Automated Molecular Dynamics Input Generation حسب Julian Konrad (9609845)

    منشور في 2025
    "…Accurately modeling chemical reactions in molecular dynamics simulations requires detailed pre- and postreaction templates, often created through labor-intensive manual workflows. …"
  10. 110

    Overview of generalized weighted averages. حسب Nobuhito Manome (8882084)

    منشور في 2025
    "…GWA-UCB1 outperformed G-UCB1, UCB1-Tuned, and Thompson sampling in most problem settings and can be useful in many situations. The code is available at <a href="https://github.com/manome/python-mab" target="_blank">https://github.com/manome/python-mab</a>.…"
  11. 111

    Overview of deep learning terminology. حسب Aaron E. Maxwell (8840882)

    منشور في 2024
    "…This paper introduces the geodl R package, which supports pixel-level classification applied to a wide range of geospatial or Earth science data that can be represented as multidimensional arrays where each channel or band holds a predictor variable. geodl is built on the torch package, which supports the implementation of DL using the R and C++ languages without the need for installing a Python/PyTorch environment. …"
  12. 112

    MCCN Case Study 3 - Select optimal survey locality حسب Donald Hobern (21435904)

    منشور في 2025
    "…</p><p dir="ltr">This is a simple implementation that uses four environmental attributes imported for all Australia (or a subset like NSW) at a moderate grid scale:</p><ol><li>Digital soil maps for key soil properties over New South Wales, version 2.0 - SEED - see <a href="https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html" target="_blank">https://esoil.io/TERNLandscapes/Public/Pages/SLGA/ProductDetails-SoilAttributes.html</a></li><li>ANUCLIM Annual Mean Rainfall raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-rainfall-raster-layer</a></li><li>ANUCLIM Annual Mean Temperature raster layer - SEED - see <a href="https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer" target="_blank">https://datasets.seed.nsw.gov.au/dataset/anuclim-annual-mean-temperature-raster-layer</a></li></ol><h4><b>Dependencies</b></h4><ul><li>This notebook requires Python 3.10 or higher</li><li>Install relevant Python libraries with: <b>pip install mccn-engine rocrate</b></li><li>Installing mccn-engine will install other dependencies</li></ul><h4><b>Overview</b></h4><ol><li>Generate STAC metadata for layers from predefined configuratiion</li><li>Load data cube and exclude nodata values</li><li>Scale all variables to a 0.0-1.0 range</li><li>Select four layers for comparison (soil organic carbon 0-30 cm, soil pH 0-30 cm, mean annual rainfall, mean annual temperature)</li><li>Select 10 random points within NSW</li><li>Generate 10 new layers representing standardised environmental distance between one of the selected points and all other points in NSW</li><li>For every point in NSW, find the lowest environmental distance to any of the selected points</li><li>Select the point in NSW that has the highest value for the lowest environmental distance to any selected point - this is the most different point</li><li>Clean up and save results to RO-Crate</li></ol><p><br></p>…"
  13. 113

    Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. حسب Adel Heydarabadipour (22290905)

    منشور في 2025
    "…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …"
  14. 114

    Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 حسب Robert Zomer (12796235)

    منشور في 2025
    "…</p><p dir="ltr">The Python programming source code used to run the calculation of ET0 and AI is provided and available online on Figshare at:</p><p dir="ltr">https://figshare.com/articles/software/Global_Aridity_Index_and_Potential_Evapotranspiration_Climate_Database_v3_-_Algorithm_Code_Python_/20005589</p><p dir="ltr">Peer-Review Reference and Proper Citation:</p><p dir="ltr">Zomer, R.J.; Xu, J.; Trabuco, A. 2022. …"
  15. 115

    Global Research Dataset on Social Media in Entrepreneurial Startup (2009–2024) حسب Lucky Ario (22115884)

    منشور في 2025
    "…Analytical outputs are organized into multiple formats: CSV files for raw bibliometric data; PNG images for thematic maps, trend topic visualizations, and research flowcharts; and CSV and PNG outputs for annual publication trajectories and polynomial regression-based modeling projections. Visualization and analysis were conducted using Microsoft Excel for summary statistics, R Biblioshiny for thematic and trend mapping, and Python for projection modeling.…"
  16. 116

    PepENS حسب Abel Chandra (16854753)

    منشور في 2025
    "…It represents a pioneering, consensus-based method by combining embeddings from ProtT5-XL-UniRef50 with Position Specific Scoring Matrices and Half-Sphere Exposure features to train an ensemble model consisting of EfficientNetB0 via image output from DeepInsight technology, CatBoost, and Logistic Regression. …"
  17. 117

    <b>Altered cognitive processes shape tactile perception in autism.</b> (data) حسب Ourania Semelidou (19178362)

    منشور في 2025
    "…The perceptual decision-making setup was controlled by Bpod (Sanworks) through scripts in Python (PyBpod, https://pybpod.readthedocs.io/en/latest/). …"
  18. 118

    GridScopeRodents: High-Resolution Global Typical Rodents Distribution Projections from 2021 to 2100 under Diverse SSP-RCP Scenarios حسب Yang Lan (20927512)

    منشور في 2025
    "…Here, <i>Genus</i> represents the rodent genus, <i>GCM</i> denotes the global climate model used, <i>Year</i> specifies the projected time period, <i>SSP-RCP</i> indicates the shared socioeconomic pathway and representative concentration pathway, and <i>Statistics</i> describes the file’s data characteristics. …"
  19. 119

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

    منشور في 2025
    "…In total, 75 % of the labelled observations were assigned to train and 25 % to test the model. To evaluate the model performance, the root mean squared root error (RMSE, the standard deviation of the residuals that represents the mean difference between the prediction and the real value for the test set) and <i>R</i><sup>2</sup> were used, which was calculated using r2_score() from <i>Scikit-learn</i> metrics. …"
  20. 120

    MYCroplanters can quantify the interaction between pathogenic and non-pathogenic bacteria and their effects on plant health. حسب Melissa Y. Chen (11301882)

    منشور في 2025
    "…(e) Figure showing data from (d) converted into binary health/disease scores. Each dot represents a single plant. Black lines with ribbons are Bayesian model predictions with 95% prediction intervals, respectively. …"