يعرض 81 - 100 نتائج من 136 نتيجة بحث عن '(( python proof implementation ) OR ( python code implemented ))', وقت الاستعلام: 0.30s تنقيح النتائج
  1. 81

    Sample data for <i>Telmatochromis temporalis</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  2. 82

    Comparison data 4 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  3. 83

    Comparison data 1 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  4. 84

    Comparison data 2 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  5. 85

    Comparison data 5 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  6. 86

    Comparison data 6 for <i>Lamprologus ocellatus</i>. حسب Nicolai Kraus (19949667)

    منشور في 2024
    "…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …"
  7. 87

    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.…"
  8. 88

    Demonstration of Isosteric Heat of Adsorption Calculation using AIFs and pyGAPs حسب Jack Evans (11275386)

    منشور في 2025
    "…</p><p dir="ltr">The calculation is performed using the Clausius-Clapeyron method as implemented in the <code><strong>pyGAPS</strong></code> Python library for adsorption science. …"
  9. 89

    Artifact for the IJCAI 2024 paper "Solving Long-run Average Reward Robust MDPs via Stochastic Games" حسب Krishnendu Chatterjee (15367413)

    منشور في 2024
    "…<br></pre></pre><h2>Structure and How to run</h2><p dir="ltr">There are four Python files in the repository.</p><pre><pre>(i) `StrategyIteration.py` is the backend code, containing the implementation of the RPPI algorithm described in the paper.…"
  10. 90

    Concurrent spin squeezing and field tracking with machine learning حسب Junlei Duan (18393642)

    منشور في 2025
    "…<p dir="ltr">The dataset contains:</p><ol><li>Steady_squeezing.zip <b>a)</b> data for steady squeezing data and characteraztion <b>b)</b> data for pulse RF magnetormeter</li><li>Tracking1.zip <b>a)</b> data of OU process for Deep learning <b>b)</b> data of OU-jump process for Deep learning</li><li>Tracking2.zip <b>a)</b> data of white noise process in backaction experiment <b>b) </b>data of white noise process in rearrange experiment</li><li>Code <b>a)</b> Randomly signal generating code <b>b)</b> Deep learning codec.data pre-processing code</li></ol><p dir="ltr">The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …"
  11. 91

    Single Cell DNA methylation data for Human Brain altas (MajorType+Region CG allc files) حسب Wubin Ding (11823941)

    منشور في 2025
    "…</p><p dir="ltr">PMID: 37824674</p><p><br></p><h2>How to download</h2><p dir="ltr">To quickly download the whole folder, Python package <a href="https://github.com/DingWB/pyfigshare" rel="noreferrer" target="_blank">pyfigshare</a> can be implemented. please refer to pyfigshare documentation: <a href="https://github.com/DingWB/pyfigshare" rel="noreferrer" target="_blank">https://github.com/DingWB/pyfigshare</a></p><p dir="ltr">for example: <code>figshare download 28424780 -o downlnoaded_data</code></p>…"
  12. 92

    Concurrent spin squeezing and field tracking with machine learning حسب Junlei Duan (18393642)

    منشور في 2025
    "…Randomly signal generating codeb.Deep learning codec.data pre-processing code The network is implemented using the torch 1.13.1 framework and CUDA 11.6 on Python 3.8.8. …"
  13. 93

    <b>Anthropogenic nutrient inputs cause excessive algal growth for nearly half the world’s population</b> حسب Richard McDowell (7311011)

    منشور في 2025
    "…<p dir="ltr">Contains</p><p dir="ltr">Final Analysis Output.xlsx: Current and reference concentrations of DRP, TP, NO3-N and TN along with pivot table analysis</p><p dir="ltr">Code: Python code used to implement the model in ArcGIS Pro.…"
  14. 94

    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>.…"
  15. 95

    Data from: Circadian activity predicts breeding phenology in the Asian burying beetle <i>Nicrophorus nepalensis</i> حسب Hao Chen (20313552)

    منشور في 2025
    "…</p><p dir="ltr">The dataset includes:</p><ol><li>Raw locomotor activity measurements (.txt files) with 1-minute resolution</li><li>Breeding experiment data (Pair_breeding.csv) documenting nest IDs, population sources, photoperiod treatments, and breeding success</li><li>Activity measurement metadata (Loc_metadataset.csv) containing detailed experimental parameters and daily activity metrics extracted using tsfresh</li></ol><p dir="ltr">The repository also includes complete analysis pipelines implemented in both Python (3.8.8) and R (4.3.1), featuring:</p><ul><li>Data preprocessing and machine learning model development</li><li>Statistical analyses</li><li>Visualization scripts for generating Shapley plots, activity pattern plots, and other figures</li></ul><p></p>…"
  16. 96

    IGD-cyberbullying-detection-AI حسب Bryan James (19921044)

    منشور في 2024
    "…</p><h2>Requirements</h2><p dir="ltr">To run this code, you'll need the following dependencies:</p><ul><li>Python 3.x</li><li>TensorFlow</li><li>scikit-learn</li><li>pandas</li><li>numpy</li><li>matplotlib</li><li>imbalanced-learn</li></ul><p dir="ltr">You can install the required dependencies using the provided <code>requirements.txt</code> file.…"
  17. 97

    The artifacts and data for the paper "DD4AV: Detecting Atomicity Violations in Interrupt-Driven Programs with Guided Concolic Execution and Filtering" (OOPSLA 2025) حسب zixuan yuan (17602152)

    منشور في 2025
    "…</li><li><ul><li><code><strong>DBDS</strong></code>: The code implements our proposed dynamic scheduling execution method, which systematically explores task interleaving for atomicity violation detection, enhanced by an effective prefix-directed strategy.…"
  18. 98

    HCC Evaluation Dataset and Results حسب Jens-Rene Giesen (18461928)

    منشور في 2024
    "…The only requirement for running this script is a Python 3.6+ interpreter as well as an installation of the <code>numpy</code> package. …"
  19. 99

    RabbitSketch حسب tong zhang (20852432)

    منشور في 2025
    "…RabbitSketch achieves significant speedups compared to existing implementations, ranging from 2.30x to 49.55x.In addition, we provide flexible and easy-to-use interfaces for both Python and C++. …"
  20. 100

    A Hybrid Ensemble-Based Parallel Learning Framework for Multi-Omics Data Integration and Cancer Subtype Classification حسب Mohammed Nasser Al-Andoli (21431681)

    منشور في 2025
    "…<p dir="ltr">The code supports replication of results on TCGA Pan-cancer and BRCA datasets and includes data preprocessing, model training, and evaluation scripts:<br>Python scripts for data preprocessing and integration</p><ul><li>Autoencoder implementation for multimodal feature learning</li><li>Hybrid ensemble training code (DL/ML models and meta-learner)</li><li>PSO and backpropagation hybrid optimization code</li><li>Parallel execution scripts</li><li>Instructions for replicating results on TCGA Pan-cancer and BRCA datasets</li></ul><p></p>…"