Showing 181 - 200 results of 322 for search '(( ((python model) OR (python code)) implementation ) OR ( python practical application ))', query time: 0.50s Refine Results
  1. 181

    Number of tweets collected per query and type. by Sylvia Iasulaitis (8301189)

    Published 2025
    “…Python algorithms were developed to model each primary collection type. …”
  2. 182

    Examples of tweets texts (English). by Sylvia Iasulaitis (8301189)

    Published 2025
    “…Python algorithms were developed to model each primary collection type. …”
  3. 183

    Users information. by Sylvia Iasulaitis (8301189)

    Published 2025
    “…Python algorithms were developed to model each primary collection type. …”
  4. 184

    The Improved Hydro-Sediment Numerical Model and Machine Learning Models by Yuning Tan (20580932)

    Published 2025
    “…The hydro-sediment model was implemented in the C# programming language using Visual Studio, while the machine learning models were developed in Python.…”
  5. 185

    Advancing Solar Magnetic Field Modeling by Carlos António (21257432)

    Published 2025
    “…<br><br>We developed a significantly faster Python code built upon a functional optimization framework previously proposed and implemented by our team. …”
  6. 186

    High-Throughput Mass Spectral Library Searching of Small Molecules in R with NIST MSPepSearch by Andrey Samokhin (20282728)

    Published 2025
    “…Despite the availability of numerous library search algorithms, those developed by NIST and implemented in MS Search remain predominant, partly because commercial databases (e.g., NIST, Wiley) are distributed in proprietary formats inaccessible to custom code. …”
  7. 187

    Comparison data 7 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  8. 188

    Sample data for <i>Neolamprologus multifasciatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  9. 189

    Sample data for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  10. 190

    Comparison data 3 for <i>Lamprologus ocellatus</i>. by Nicolai Kraus (19949667)

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  11. 191

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

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  12. 192

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

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  13. 193

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

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  14. 194

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

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  15. 195

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

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  16. 196

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

    Published 2024
    “…TIBA accepts data outputs from popular logging software and is implemented in Python and JavaScript, with all current browsers supported. …”
  17. 197

    A multi-hop example from the BibSQL dataset. by Zhenyu Wang (580934)

    Published 2025
    “…While acknowledging limitations such as potential logic errors in complex queries and reliance on domain-specific knowledge, the proposed framework shows strong generalizability and practical applicability. By uniquely integrating semantic similarity learning, RAG, and PoT prompting, this work establishes a scalable foundation for future intelligent bibliographic retrieval systems and domain-specific Text-to-SQL applications.…”
  18. 198

    Detailed statistics of the BibSQL dataset. by Zhenyu Wang (580934)

    Published 2025
    “…While acknowledging limitations such as potential logic errors in complex queries and reliance on domain-specific knowledge, the proposed framework shows strong generalizability and practical applicability. By uniquely integrating semantic similarity learning, RAG, and PoT prompting, this work establishes a scalable foundation for future intelligent bibliographic retrieval systems and domain-specific Text-to-SQL applications.…”
  19. 199

    Linking Thermal Conductivity to Equations of State Using the Residual Entropy Scaling Theory by Zhuo Li (165589)

    Published 2024
    “…Besides, a detailed examination of the impact of the critical enhancement term on mixture calculations was conducted. To use our model easily, a software package written in Python is provided in the Supporting Information.…”
  20. 200

    Overview of deep learning terminology. by Aaron E. Maxwell (8840882)

    Published 2024
    “…This paper introduces the geodl R package, which supports pixel-level classification applied to a wide range of geospatial or Earth science data that can be represented as multidimensional arrays where each channel or band holds a predictor variable. geodl is built on the torch package, which supports the implementation of DL using the R and C++ languages without the need for installing a Python/PyTorch environment. …”