Showing 141 - 160 results of 280 for search '(( python model implementation ) OR ( python from implementing ))', query time: 0.28s Refine Results
  1. 141

    Hippocampal and cortical activity reflect early hyperexcitability in an Alzheimer's mouse model by Marina Diachenko (19739092)

    Published 2025
    “…</p><p dir="ltr">All data are available upon request. The standalone Python implementation of the fE/I algorithm is available under a CC-BY-NC-SA license at <a href="https://github.com/arthur-ervin/crosci" target="_blank">https://github.com/arthur-ervin/crosci</a>. …”
  2. 142

    Iterative Methods for Vecchia-Laplace Approximations for Latent Gaussian Process Models by Pascal Kündig (19824557)

    Published 2024
    “…In particular, we obtain a speed-up of an order of magnitude compared to Cholesky-based calculations and a 3-fold increase in prediction accuracy in terms of the continuous ranked probability score compared to a state-of-the-art method on a large satellite dataset. All methods are implemented in a free C++ software library with high-level Python and R packages. …”
  3. 143

    Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil) by Amanda Bueno de Moraes (22559249)

    Published 2025
    “…<p dir="ltr">This deposit provides the Python notebook and the input dataset used in the study “Numerical analysis and modeling of water quality indicators in the Ribeirão João Leite reservoir (Goiás, Brazil).” …”
  4. 144

    Neural-Signal Tokenization and Real-Time Contextual Foundation Modelling for Sovereign-Scale AGI Systems by Lakshit Mathur (20894549)

    Published 2025
    “…The work advances national AI autonomy, real-time cognitive context modeling, and ethical human-AI integration.</p><p dir="ltr"><b>Availability</b> — The repository includes LaTeX sources, trained model checkpoints, Python/PyTorch code, and synthetic datasets. …”
  5. 145

    DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

    Published 2024
    “…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”
  6. 146

    DataSheet1_Prostruc: an open-source tool for 3D structure prediction using homology modeling.PDF by Shivani V. Pawar (20355171)

    Published 2024
    “…</p>Methods<p>Prostruc is a Python-based homology modeling tool designed to simplify protein structure prediction through an intuitive, automated pipeline. …”
  7. 147

    Code for High-quality Human Activity Intensity Maps in China from 2000-2020 by Wenqi Xie (18273238)

    Published 2025
    “…<p dir="ltr">Code and remote sensing images and interpretation results of the samples for uncertainty analysis for "High-quality Human Activity Intensity Maps in China from 2000-2020"</p><p dir="ltr">“Mapping_HAI.py”:We generated the HAI maps using ArcGIS 10.8, and the geoprocessing tasks were implemented using Python 2.7 with the ArcPy library (ArcGIS 10.8 + Python 2.7 environment). …”
  8. 148
  9. 149

    face recognation with Flask by Muammar, SST, M.Kom (21435692)

    Published 2025
    “…Built using the <b>Flask</b> web framework (Python), this system provides a lightweight and scalable solution for implementing facial recognition capabilities in real-time or on-demand through a browser interface.…”
  10. 150

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

    Published 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>…”
  11. 151
  12. 152

    Image 1_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif by Xiaobing Li (291454)

    Published 2025
    “…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”
  13. 153

    Image 2_Differential diagnosis of pneumoconiosis mass shadows and peripheral lung cancer using CT radiomics and the AdaBoost machine learning model.tif by Xiaobing Li (291454)

    Published 2025
    “…LR, SVM, and AdaBoost algorithms were implemented using Python to build the models. In the training set, the accuracies of the LR, SVM, and AdaBoost models were 79.4, 84.0, and 80.9%, respectively; the sensitivities were 74.1, 74.1, and 81.0%, respectively; the specificities were 83.6, 91.8, and 80.8%, respectively; and the AUC values were 0.837, 0.886, and 0.900, respectively. …”
  14. 154

    Data&Codes.zip by Zer0 Star (20545655)

    Published 2025
    “…</p><p dir="ltr">To facilitate the widespread use of the proposed framework, we have implemented it as the <b><i>ESLocalIndi</i></b> open-source package in Python, making it easily accessible to geographers. …”
  15. 155

    Supplementary file 1_ParaDeep: sequence-based deep learning for residue-level paratope prediction using chain-aware BiLSTM-CNN models.docx by Piyachat Udomwong (22563212)

    Published 2025
    “…The implementation is freely available at https://github.com/PiyachatU/ParaDeep, with Python (PyTorch) code and a Google Colab interface for ease of use.…”
  16. 156

    Collaborative Research: Framework: Improving the Understanding and Representation of Atmospheric Gravity Waves using High-Resolution Observations and Machine Learning by Joan Alexander (17047170)

    Published 2025
    “…Establishing a framework for implementing and testing ML-based parameterizations in atmospheric models. …”
  17. 157

    Genosophus: A Dynamical-Systems Diagnostic Engine for Neural Representation Analysis by Alan Glanz (22109698)

    Published 2025
    “…</b><code><strong>GenosophusV2.py</strong></code></h3><p dir="ltr">Executable Python implementation of the Genosophus Engine.</p><h3><b>2. …”
  18. 158

    Data and software for "Social networks affect redistribution decisions and polarization" by Milena Tsvetkova (11217969)

    Published 2025
    “…<p dir="ltr">Data from agent based models and experiments with human participants recruited from Prolific, together with code for the models and analysis. …”
  19. 159

    Missing Value Imputation in Relational Data Using Variational Inference by Simon Fontaine (7046618)

    Published 2025
    “…Additional results, implementation details, a Python implementation, and the code reproducing the results are available online. …”
  20. 160

    Parallel Sampling of Decomposable Graphs Using Markov Chains on Junction Trees by Mohamad Elmasri (19421498)

    Published 2024
    “…We find that our parallel sampler yields improved mixing properties in comparison to the single-move variate, and outperforms current state-of-the-art methods in terms of accuracy and computational efficiency. The implementation of our work is available in the Python package parallelDG. …”