يعرض 181 - 200 نتائج من 286 نتيجة بحث عن '((python model) OR (python code)) implemented', وقت الاستعلام: 0.24s تنقيح النتائج
  1. 181

    Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models حسب Pascal Kündig (19824557)

    منشور في 2024
    "…In particular, we obtain a speed-up of an order of magnitude compared to Cholesky-based calculations and a 3-fold increase in prediction accuracy in terms of the continuous ranked probability score compared to a state-of-the-art method on a large satellite dataset. All methods are implemented in a free C++ software library with high-level Python and R packages. …"
  2. 182

    Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) حسب Amanda Bueno de Moraes (22559249)

    منشور في 2025
    "…The code implements a statistical–computational workflow for parameter selection (VIF, Bartlett and KMO tests, PCA and FA with <i>varimax</i>) and then trains and evaluates machine-learning models to predict three key physico-chemical indicators: turbidity, true color, and total iron. …"
  3. 183

    Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems حسب Lakshit Mathur (20894549)

    منشور في 2025
    "…The work advances national AI autonomy, real-time cognitive context modeling, and ethical human-AI integration.</p><p dir="ltr"><b>Availability</b> — The repository includes LaTeX sources, trained model checkpoints, Python/PyTorch code, and synthetic datasets. …"
  4. 184

    face recognation with Flask حسب Muammar, SST, M.Kom (21435692)

    منشور في 2025
    "…</li><li><b>Face Recognition Engine:</b> Compares detected faces to known faces using deep learning models (e.g., <code>face_recognition</code>, based on dlib’s ResNet).…"
  5. 185

    DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF حسب Shivani V. Pawar (20355171)

    منشور في 2024
    "…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …"
  6. 186

    DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF حسب Shivani V. Pawar (20355171)

    منشور في 2024
    "…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …"
  7. 187

    Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis حسب Alan Glanz (22109698)

    منشور في 2025
    "…</p><h2><b>Included Files</b></h2><h3><b>1. </b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.…"
  8. 188

    Image 1_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif حسب Xiaobing Li (291454)

    منشور في 2025
    "…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …"
  9. 189

    Image 2_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif حسب Xiaobing Li (291454)

    منشور في 2025
    "…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …"
  10. 190
  11. 191

    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.…"
  12. 192

    Data and software for "Social networks affect redistribution decisions and polarization" حسب Milena Tsvetkova (11217969)

    منشور في 2025
    "…</p><p dir="ltr">The repository contains data in .csv and .xlsx format, model code in .nlogox Netlogo format, analysis code in .ipynb Jupyter notebooks, and helping code in .py Python files.…"
  13. 193

    Collaborative Research: Framework: Improving the Understanding and Representation of Atmospheric Gravity Waves using High-Resolution Observations and Machine Learning حسب Joan Alexander (17047170)

    منشور في 2025
    "…Establishing a framework for implementing and testing ML-based parameterizations in atmospheric models. …"
  14. 194

    Missing Value Imputation in Relational Data Using Variational Inference حسب Simon Fontaine (7046618)

    منشور في 2025
    "…Additional results, implementation details, a Python implementation, and the code reproducing the results are available online. …"
  15. 195

    Supporting data for "Software library to quantify the value of forecasts for decision-making: Case study on sensitivity to damages" by Laugesen et al. (2025) حسب Richard Laugesen (6480371)

    منشور في 2025
    "…<br></p><p dir="ltr">Journal paper introduces RUVPY, a Python software library which implements the Relative Utility Value (RUV) method. …"
  16. 196

    Parallel Sampling of Decomposable Graphs Using Markov Chains on Junction Trees حسب Mohamad Elmasri (19421498)

    منشور في 2024
    "…We find that our parallel sampler yields improved mixing properties in comparison to the single-move variate, and outperforms current state-of-the-art methods in terms of accuracy and computational efficiency. The implementation of our work is available in the Python package parallelDG. …"
  17. 197

    Recursive generation of substructures using point data حسب Jackie R (18359715)

    منشور في 2025
    "…<p dir="ltr">The dataset contains generated substructure using POI in China, the pseudo code for the algorithm and python implement of the algorithm. …"
  18. 198

    <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/). …"
  19. 199

    Spotted owl habitat quality maps and disturbance attribution analysis حسب Josh Barry (7573823)

    منشور في 2025
    "…<p dir="ltr">This dataset includes annual spatial maps of spotted owl nesting habitat quality in Southern California and an accompanying ArcPython script used to attribute negative annual habitat change to wildfire (Barry et al., 2025). …"
  20. 200

    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>…"