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from implementing » after implementing (Expand Search), _ implementing (Expand Search)
python model » python tool (Expand Search), action model (Expand Search), motion model (Expand Search)
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121
Simulation Code and Raw Data
Published 2025“…<p dir="ltr">Reproducible code (Python) implementing a symmetrized split-step Fourier method (SSFM), with configuration files for all scans. …”
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RealBench: A Repo-Level Code Generation Benchmark Aligned with Real-World Software Development Practices
Published 2025“…<br>│ │ └── uml_dag.py # UML dependency graph analysis.<br>│ ├── model_gen/ # Code generation using various LLMs.<br>│ │ ├── generate/ # LLM inference implementations.…”
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software code of NeoDesign
Published 2024“…<h2>Implementation and Dependencies</h2><p dir="ltr">neoDesign was developed with python (recommend>3.9) and shell (bash) language. …”
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<b>Code and derived data for</b><b>Training Sample Location Matters: Accuracy Impacts in LULC Classification</b>
Published 2025“…</li><li>Python/Kaggle notebooks (<code>.ipynb</code>): reproducibility pipeline for accuracy metrics and statistical analysis.…”
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125
A game of life with dormancy - Code
Published 2024“…</p><ul><li>To run an animated simulation, use `python simulation.py'.</li><li>The implementation of Spore Life can be found in gol.py.…”
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The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation"
Published 2025“…The model results are saved in <code>1point2dem/SampleGeneration/result</code>, and the results for <b>Table 3</b> in the paper are derived from this output.…”
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The codes and data for "A Graph Convolutional Neural Network-based Method for Predicting Computational Intensity of Geocomputation"
Published 2025“…The model results are saved in <code>1point2dem/SampleGeneration/result</code>, and the results for <b>Table 3</b> in the paper are derived from this output.…”
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Performance comparison of cyber security techniques in IoMT healthcare devices.
Published 2025Subjects: -
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Data and code for: Automatic fish scale analysis
Published 2025“…</p><h3>Includeed in this repository:</h3><ul><li><b>Raw data files:</b></li><li><code>comparison_all_scales.csv</code> – comparison_all_scales.csv - manually verified vs. automated measurements of 1095 coregonid scales</li></ul><ul><li><ul><li><code>Validation_data.csv</code> – manually measured scale data under binocular</li><li><code>Parameter_correction_numeric.csv</code> – calibration data (scale radius vs. fish length/weight)</li></ul></li><li><b>Statistical results:</b></li><li><ul><li><code>comparison_stats_core_variables.csv</code> – verification statistics (bias, relative error, limits of agreement)</li><li><code>Validation_statistics.csv</code> – summary statistics and model fits (manual vs. automated)</li></ul></li><li><b>Executable script (not GUI):</b></li><li><ul><li><code>Algorithm.py</code> – core processing module for scale feature extraction<br>→ <i>Note: The complete Coregon Analyzer application (incl. …”
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Testing Code for JcvPCA and JsvCRP.
Published 2025“…<p>This file contains the code that implements both metrics in python and apply them on a simulated dataset.…”
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Data and some code used in the paper:<b>Expansion quantization network: A micro-emotion detection and annotation framework</b>
Published 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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Overview of deep learning terminology.
Published 2024“…Training loops are implemented with the luz package. The geodl package provides utility functions for creating raster masks or labels from vector-based geospatial data and image chips and associated masks from larger files and extents. …”
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A comparison between the static Python-based visualizations of the p65 activity in activated fibroblasts and the dynamic, HTML-based visualizations that use these same reduction me...
Published 2025“…<p><b>(a)</b> UMAP, t-SNE, PCA, and Diffmap were first generated using the Python libraries Scikit-learn, UMAP, and PyDiffmap within Jupyter to generate static graphs as a starting point. …”