يعرض 161 - 180 نتائج من 213 نتيجة بحث عن '(( ((python tool) OR (python code)) implementing ) OR ( python time implementation ))', وقت الاستعلام: 0.27s تنقيح النتائج
  1. 161

    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++. …"
  2. 162

    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>…"
  3. 163

    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. …"
  4. 164

    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. …"
  5. 165

    MSc Personalised Medicine at Ulster University حسب Steven Watterson (100045)

    منشور في 2025
    "…</b> Introducing computational approaches to studying genes, proteins or metabolites, this module teaches Python coding, data analysis and how to work with the databases that support data analysis.…"
  6. 166

    <b>Algorithm Pseudocode</b> حسب Yibin Zhao (22425801)

    منشور في 2025
    "…The model generates point forecasts and forecast interval boundaries for short-term loads, providing important support for risk quantification and decision-making in power systems. The pseudo-code follows standard Python syntax specifications for functions and loops and is easy to understand and implement. …"
  7. 167

    <b>Anonymous, runnable artifact for </b><b>Testing AI Applications Under Nondeterminism, Drift, and Resource Constraints: A Problem‑Driven Multi‑Layer Approach</b> حسب Nariman Mani (21380459)

    منشور في 2025
    "…</b> The anonymized archive includes a dependency‑free Python implementation of all five layers (oracle, coverage, drift mapping, prioritization, resource scheduling), an orchestrator, and synthetic datasets with 50 test cases per sub‑application (LLM assistant, retrieval with citation, vision calories, notification/social). …"
  8. 168

    <b>Testing AI Applications Under Nondeterminism, Drift, and Resource Constraints</b> حسب Nariman Mani (21380459)

    منشور في 2025
    "…<ul><li>A <b>Python repo</b> with minimal implementations of all five layers<br>(<b>COL</b>, <b>SCL</b>, <b>CDM</b>, <b>RPE</b>, <b>RAS</b>) plus an <b>orchestrator</b> and utilities.…"
  9. 169

    Soulware-Lite حسب Abhiram Gnyanijaya (21572942)

    منشور في 2025
    "…It operates as middleware to intercept user inputs and LLM outputs, performing real-time semantic auditing, belief-state tracking, introspective alignment scoring (KRW, deltaΨ), and automated self-correction.…"
  10. 170

    PYSEQM 2.0: Accelerated Semiempirical Excited-State Calculations on Graphical Processing Units حسب Vishikh Athavale (12623809)

    منشور في 2025
    "…We report the development and implementation of electronic excited-state capabilities for semiempirical quantum chemical methods at both the Configuration Interaction Singles and Time-Dependent Hartree–Fock levels of theory, integrated within the PYSEQM 2.0 software package (https://github.com/lanl/PYSEQM). …"
  11. 171

    Curvature-Adaptive Embedding of Geographic Knowledge Graphs in Hyperbolic Space حسب chenchen Guo (21327470)

    منشور في 2025
    "…</p><h3>Requirements</h3><ul><li>Python 3.7</li><li>PyTorch 1.10.0 & CUDA 11.8</li></ul><h3>Main Result Running commands:</h3><p dir="ltr">Execute <code>.sh: bash .…"
  12. 172

    A Fully Configurable Open-Source Software-Defined Digital Quantized Spiking Neural Core Architecture حسب Nagarajan Kandasamy (8400168)

    منشور في 2025
    "…QUANTISENC’s software-defined hardware design methodology allows the user to train an SNN model using Python and evaluate performance of its hardware implementation, such as area, power, latency, and throughput. …"
  13. 173

    adnus حسب Mehmet Keçeci (14301782)

    منشور في 2025
    "…<p dir="ltr">adnus (AdNuS): Advanced Number Systems</p><p dir="ltr">adnus is a Python library that provides an implementation of various advanced number systems. …"
  14. 174

    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. …"
  15. 175

    Leveraging explainable causal artificial intelligence to study forest gross primary productivity dynamics in China's protected areas حسب Pedro Cabral (18947566)

    منشور في 2025
    "…<p dir="ltr">A Python script used for modeling forest GPP in China´s Protected Areas, including mean encoding of the categorical variable climate zone (CZ), multicollinearity testing using Variance Inflation Factor (VIF), implementation of four machine learning models to predict forest GPP, XAI and causality analysis.…"
  16. 176

    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. …"
  17. 177

    Computational performance analysis script. حسب Le Qi (8859521)

    منشور في 2025
    "…<p>Python implementation for computational performance evaluation and timing analysis.…"
  18. 178

    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>…"
  19. 179

    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.…"
  20. 180

    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>.…"