يعرض 41 - 60 نتائج من 287 نتيجة بحث عن '(( python ((code implementation) OR (modular implementation)) ) OR ( python model implementing ))', وقت الاستعلام: 0.34s تنقيح النتائج
  1. 41
  2. 42

    Performance Benchmark: SBMLNetwork vs. SBMLDiagrams Auto-layout. حسب Adel Heydarabadipour (22290905)

    منشور في 2025
    "…<p>Log–log plot of median wall-clock time for SBMLNetwork’s C++-based auto-layout engine (blue circles, solid fit) and SBMLDiagrams’ implementation of the pure-Python NetworkX spring_layout algorithm (red squares, dashed fit), applied to synthetic SBML models containing 20–2,000 species, with a fixed 4:1 species-to-reaction ratio. …"
  3. 43
  4. 44
  5. 45
  6. 46
  7. 47

    Exploring the integration of metaverse technologies in engineering education through the SAMR model حسب Snezhana Dineva (22444471)

    منشور في 2025
    "…The final deliverable is a plan for phased integration of metaverse learning into a Python programming course following this model, building on existing best practices.…"
  8. 48
  9. 49
  10. 50

    2D Orthogonal Planes Split: <b>Python</b> and <b>MATLAB</b> code | <b>Source Images</b> for Figures حسب Nektarios Valous (20715650)

    منشور في 2025
    "…The output files generated by the code include results from both Python and MATLAB implementations; these output images are provided as validation, demonstrating that both implementations produce matching results.…"
  11. 51

    EFGs: A Complete and Accurate Implementation of Ertl’s Functional Group Detection Algorithm in RDKit حسب Gonzalo Colmenarejo (650249)

    منشور في 2025
    "…In this paper, a new RDKit/Python implementation of the algorithm is described, that is both accurate and complete. …"
  12. 52
  13. 53

    Workflow of a typical Epydemix run. حسب Nicolò Gozzi (8837522)

    منشور في 2025
    "…<div><p>We present Epydemix, an open-source Python package for the development and calibration of stochastic compartmental epidemic models. …"
  14. 54
  15. 55

    The format of the electrode csv file حسب Joseph James Tharayil (21416715)

    منشور في 2025
    "…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …"
  16. 56

    The format of the simulation reports حسب Joseph James Tharayil (21416715)

    منشور في 2025
    "…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …"
  17. 57

    Comparison of BlueRecording with existing tools حسب Joseph James Tharayil (21416715)

    منشور في 2025
    "…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …"
  18. 58

    The format of the weights file حسب Joseph James Tharayil (21416715)

    منشور في 2025
    "…To enable efficient calculation of extracellular signals from large neural network simulations, we have developed <i>BlueRecording</i>, a pipeline consisting of standalone Python code, along with extensions to the Neurodamus simulation control application, the CoreNEURON computation engine, and the SONATA data format, to permit online calculation of such signals. …"
  19. 59

    Cost functions implemented in Neuroptimus. حسب Máté Mohácsi (20469514)

    منشور في 2024
    "…To address these issues, we developed a generic platform (called Neuroptimus) that allows users to set up neural parameter optimization tasks via a graphical interface, and to solve these tasks using a wide selection of state-of-the-art parameter search methods implemented by five different Python packages. Neuroptimus also offers several features to support more advanced usage, including the ability to run most algorithms in parallel, which allows it to take advantage of high-performance computing architectures. …"
  20. 60