يعرض 221 - 240 نتائج من 258 نتيجة بحث عن '((python model) OR (python tool)) implementing', وقت الاستعلام: 0.28s تنقيح النتائج
  1. 221

    Automatic data reduction for the typical astronomer حسب Bradford Holden (21789524)

    منشور في 2025
    "…PypeIt has been developed by a small team of astronomers with two leading philosophies: (1) build instrument-agnostic code to serve nearly any spectrograph; (2) implement algorithms that achieve Poisson-level sky-subtraction with minimal systematics to yield precisely calibrated spectra with a meaningful noise model. …"
  2. 222

    Bayesian Changepoint Detection via Logistic Regression and the Topological Analysis of Image Series حسب Andrew M. Thomas (712104)

    منشور في 2025
    "…The method also successfully recovers the location and nature of changes in more traditional changepoint tasks. An implementation of our method is available in the Python package bclr.…"
  3. 223

    Evaluation and Statistical Analysis Code for "Multi-Task Learning for Joint Fisheye Compression and Perception for Autonomous Driving" حسب Basem Ahmed (18127861)

    منشور في 2025
    "…</li></ul><p dir="ltr">These scripts are implemented in Python using the PyTorch framework and are provided to ensure the reproducibility of the experimental results presented in the manuscript.…"
  4. 224

    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. …"
  5. 225

    Copy number contingency table. حسب Yang Wu (66682)

    منشور في 2025
    "…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…"
  6. 226

    Gene mutation contingency table. حسب Yang Wu (66682)

    منشور في 2025
    "…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…"
  7. 227

    Resistant & sensitive cell line Info on AZD5991. حسب Yang Wu (66682)

    منشور في 2025
    "…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…"
  8. 228

    Resistant & sensitive drug info on COLO800. حسب Yang Wu (66682)

    منشور في 2025
    "…Our methods are implemented in Python and are freely available from GitHub (<a href="https://github.com/queryang/PASO" target="_blank">https://github.com/queryang/PASO</a>).…"
  9. 229

    Supplementary Data: Biodiversity and Energy System Planning - Queensland 2025 حسب Andrew Rogers (17623239)

    منشور في 2025
    "…</p><h2>Software and Spatial Resolution</h2><p dir="ltr">The VRE siting model is implemented using Python and relies heavily on ArcGIS for comprehensive spatial data handling and analysis.…"
  10. 230

    Methodological Approach Based on Structural Parameters, Vibrational Frequencies, and MMFF94 Bond Charge Increments for Platinum-Based Compounds حسب Gloria Castañeda-Valencia (20758502)

    منشور في 2025
    "…The developed bci optimization tool, based on MMFF94, was implemented using a Python code made available at https://github.com/molmodcs/bci_solver. …"
  11. 231

    Code حسب Baoqiang Chen (21099509)

    منشور في 2025
    "…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …"
  12. 232

    Core data حسب Baoqiang Chen (21099509)

    منشور في 2025
    "…We divided the dataset into training and test sets, using 70% of the genes for training and 30% for testing. We implemented machine learning algorithms using the following R packages: rpart for Decision Trees, gbm for Gradient Boosting Machines (GBM), ranger for Random Forests, the glm function for Generalized Linear Models (GLM), and xgboost for Extreme Gradient Boosting (XGB). …"
  13. 233

    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>…"
  14. 234

    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.…"
  15. 235

    Summary of Tourism Dataset. حسب Jing Zhang (23775)

    منشور في 2025
    "…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …"
  16. 236

    Segment-wise Spending Analysis. حسب Jing Zhang (23775)

    منشور في 2025
    "…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …"
  17. 237

    Hyperparameter Parameter Setting. حسب Jing Zhang (23775)

    منشور في 2025
    "…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …"
  18. 238

    Marketing Campaign Analysis. حسب Jing Zhang (23775)

    منشور في 2025
    "…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …"
  19. 239

    Visitor Segmentation Validation Accuracy. حسب Jing Zhang (23775)

    منشور في 2025
    "…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …"
  20. 240

    Integration of VAE and RNN Architecture. حسب Jing Zhang (23775)

    منشور في 2025
    "…The implementation uses Python language on a tourism dataset comprising necessary attributes like visitor numbers, days, spending patterns, employment, international tourism samples over a specific region, and a diverse age group analyzed over a year. …"