يعرض 21 - 25 نتائج من 25 نتيجة بحث عن '(( binary basic column optimization algorithm ) OR ( library based robust optimization algorithm ))', وقت الاستعلام: 0.26s تنقيح النتائج
  1. 21

    Code حسب Baoqiang Chen (21099509)

    منشور في 2025
    "…</p><p><br></p><p dir="ltr">This architecture was implemented using the PyTorch library and trained using cross-entropy loss. The model was optimized to classify RNA sequences, achieving robust performance across multiple test sets.…"
  2. 22

    Core data حسب Baoqiang Chen (21099509)

    منشور في 2025
    "…</p><p><br></p><p dir="ltr">This architecture was implemented using the PyTorch library and trained using cross-entropy loss. The model was optimized to classify RNA sequences, achieving robust performance across multiple test sets.…"
  3. 23

    Minisymposterium: Muq-Hippylib: A Bayesian Inference Software Framework Integrating Data with Complex Predictive Models under Uncertainty حسب Ki-Tae Kim (10184066)

    منشور في 2021
    "…By integrating these two libraries, we created a robust, scalable, efficient and productive software framework that realizes the benefits of each to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering areas.…"
  4. 24

    SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion حسب Omar Ghattas (4387300)

    منشور في 2020
    "…By integrating these two libraries, we created a robust, scalable, and efficient software framework that realizes the benefits of each to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering areas.…"
  5. 25

    SI2-SSI: Integrating Data with Complex Predictive Models under Uncertainty: An Extensible Software Framework for Large-Scale Bayesian Inversion حسب Umberto Villa (8400192)

    منشور في 2020
    "…By integrating these two libraries, we created a robust, scalable, and efficient software framework that realizes the benefits of each to tackle complex large-scale Bayesian inverse problems across a broad spectrum of scientific and engineering areas.…"