بدائل البحث:
model implementation » modular implementation (توسيع البحث), world implementation (توسيع البحث), time implementation (توسيع البحث)
code representing » model representing (توسيع البحث), models representing (توسيع البحث), tpd representing (توسيع البحث)
python model » python tool (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
model implementation » modular implementation (توسيع البحث), world implementation (توسيع البحث), time implementation (توسيع البحث)
code representing » model representing (توسيع البحث), models representing (توسيع البحث), tpd representing (توسيع البحث)
python model » python tool (توسيع البحث), action model (توسيع البحث), motion model (توسيع البحث)
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201
The codes and data for "Lane Extraction from Trajectories at Road Intersections Based on Graph Transformer Network"
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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202
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Data files accompanying our PLoS One publication
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>
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.…"
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207
Probabilistic-QSR-GeoQA
منشور في 2024"…Also we have written Python API for Probcog (ProbCog-API.py) and SparQ reasoners (SparQ-API.py).…"
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208
Code and data for reproducing the results in the original paper of DML-Geo
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.…"
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209
Accompanying data files (Melbourne, Washington DC, Singapore, and NYC-Manhattan)
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"
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"
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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Leue Modulation Coefficients (LMC): A Smooth Continuum Embedding of Bounded Arithmetic Data
منشور في 2025"…This Zenodo package includes: the full research paper (PDF), a complete Python implementation generating the LMC field and conductivity model, a numerical plot comparing discrete LMC values with the smoothed continuum field, a cover letter and supporting documentation. …"
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213
Error reduction over time by the HOFA-SMC.
منشور في 2025"…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …"
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Comparison of SMC techniques.
منشور في 2025"…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …"
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215
Proposed HOFA-SMC with experimental validation.
منشور في 2025"…A detailed simulation study is conducted on a full hand model, comprising four 4-degree-of-freedom (DOF) fingers and a 3-DOF thumb, implemented in Python. …"
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216
ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation
منشور في 2025"…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …"
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ReaxANA: Analysis of Reactive Dynamics Trajectories for Reaction Network Generation
منشور في 2025"…To address this challenge, we introduce a graph algorithm-based explicit denoising approach that defines user-controlled operations for removing oscillatory reaction patterns, including combination and separation, isomerization, and node contraction. This algorithm is implemented in ReaxANA, a parallel Python package designed to extract reaction mechanisms from both heterogeneous and homogeneous reactive MD trajectories. …"
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Overview of generalized weighted averages.
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>.…"
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Dataset for CNN-based Bayesian Calibration of TELEMAC-2D Hydraulic Model
منشور في 2025"…</li><li>Files starting with <code>y_part</code> are flattened output arrays representing corresponding water depth values.…"
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Moulin distributions during 2016-2021 on the southwest Greenland Ice Sheet
منشور في 2025"…</p><p><br></p><ul><li>00_Satellite-derived moulins: Moulins directly mapped from Sentinel-2 imagery, representing actual moulin positions;</li><li>01_Snapped moulins: Moulins snapped to DEM-modeled supraglacial drainage networks, primarily used for analyses;</li><li>02_Moulin recurrences: Recurring moulins determined from the snapped moulins;</li><li>03_Internally drained catchments: Internally drained catchment (IDC) associated with each moulin;</li><li>04_Surface meltwater runoff: surface meltwater runoff calculated from MAR for the study area, elevation bins, and IDCs; </li><li>05_DEM-derived: Topographic features modeled from ArcticDEM, including elevation bins, depressions and drainage networks;</li><li>06_GWR: Variables for conducting geographically weighted regression (GWR) analysis;</li></ul><p><br></p><ul><li>Code_01_Mapping moulins on the southwestern GrIS.ipynb: A Jupyter Notebook to analyze moulin distributions, reproducing most of the analyses and figures presented in the manuscript using the provided datasets;</li><li>Code_02_pre1_calculate Strain Rate from XY ice velocity.py: A preprocessing Python script to calculate strain rate for the GWR analysis;</li><li>Code_02_pre2_calculate Driving Stress from ice thickness and surface slope.py: A preprocessing Python script to calculate driving stress for the GWR analysis;</li><li>Code_02_GWR analysis.ipynb: A Jupyter Notebook to conduct the GWR analysis using the provided datasets.…"