يعرض 141 - 160 نتائج من 229 نتيجة بحث عن 'python model implementation', وقت الاستعلام: 0.10s تنقيح النتائج
  1. 141

    <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/). …"
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    Cathode carbon block material parameters [14]. حسب Chenglong Gong (20629836)

    منشور في 2025
    "…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"
  5. 145

    Sodium concentration distribution cloud map. حسب Chenglong Gong (20629836)

    منشور في 2025
    "…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"
  6. 146

    Sodium binding coefficient R. حسب Chenglong Gong (20629836)

    منشور في 2025
    "…A random aggregate model was implemented in Python and imported into finite element software to simulate sodium diffusion using Fick’s second law. …"
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    The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network" حسب Chongshan Wan (19247614)

    منشور في 2024
    "…</p><h3><b>Model training</b></h3><h4><code>python train_GTN.py</code></h4><p dir="ltr">This step trains the GTN model. …"
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    Global Aridity Index and Potential Evapotranspiration (ET0) Database: Version 3.1 حسب Robert Zomer (12796235)

    منشور في 2025
    "…The database also includes three averaged multi-model ensembles produced for each of the four emission scenarios:</p><p>**************************************************************************************************************************</p><p dir="ltr">The Global Aridity Index (Global-AI) and Global Reference Evapo-Transpiration (Global-ET0) datasets provided in Version 3.1 of the Global Aridity Index and Potential Evapo-Transpiration (ET0) Database (Global-AI_PET_v3.x1) provide high-resolution (30 arc-seconds) global raster data for the 1970-2000 period, related to evapotranspiration processes and rainfall deficit for potential vegetative growth, based upon implementation of the FAO-56 Penman-Monteith Reference Evapotranspiration (ET<sub>0</sub>) equation.…"
  13. 153

    Data files accompanying our PLoS One publication حسب Peter Hinow (21810605)

    منشور في 2025
    "…The videos were digitized and the positional data were saved in .xlsx or .csv format, respectively. The python codes contain the numerical implementations of our mathematical models.…"
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    Data and some code used in the paper:<b>Expansion quantization network: A micro-emotion detection and annotation framework</b> حسب Zhou (20184816)

    منشور في 2025
    "…</p><p dir="ltr">GPU:NVIDIA GeForce RTX 3090 GPU</p><p dir="ltr">Bert-base-cased pre-trained model: https://huggingface.co/google-bert/bert-base-cased</p><p dir="ltr">python=3.7,pytorch=1.9.0,cudatoolkit=11.3.1,cudnn=8.9.7.29.…"
  16. 156

    Probabilistic-QSR-GeoQA حسب Mohammad Kazemi (19442467)

    منشور في 2024
    "…Also we have written Python API for Probcog (ProbCog-API.py) and SparQ reasoners (SparQ-API.py).…"
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    Code and data for reproducing the results in the original paper of DML-Geo حسب Pengfei CHEN (8059976)

    منشور في 2025
    "…<p dir="ltr">This asset provides all the code and data for reproducing the results (figures and statistics) in the original paper of DML-Geo</p><h2>Main Files:</h2><p dir="ltr"><b>main.ipynb</b>: the main notebook to generate all the figures and data presented in the paper</p><p dir="ltr"><b>data_generator.py</b>: used for generating synthetic datasets to validate the performance of different models</p><p dir="ltr"><b>dml_models.py</b>: Contains implementations of different Double Machine Learning variants used in this study.…"
  18. 158

    Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan) حسب Winston Yap (13771969)

    منشور في 2025
    "…</p><p dir="ltr">Each zipped folder consists the following files:</p><ul><li>Graph data - City object nodes (.parquet) and COO format edges (.txt)</li><li>predictions.txt (model predictions from GraphSAGE model)</li><li>final_energy.parquet (Compiled training and validation building energy data)</li></ul><p dir="ltr">The provided files are supplementary to the code repository which provides Python notebooks stepping through the data preprocessing, GNN training, and satellite imagery download processes. …"
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    The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" حسب FirstName LastName (20554465)

    منشور في 2025
    "…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"
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    The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation" حسب FirstName LastName (20554465)

    منشور في 2025
    "…</p><p dir="ltr"><i>cd 1point2dem/CIPrediction</i></p><p dir="ltr"><i>python -u point_prediction.py --model [GCN|ChebNet|GATNet]</i></p><h3>step 4: Parallel computation</h3><p dir="ltr">This step uses the trained models to optimize parallel computation. …"