Showing 141 - 160 results of 12,609 for search '(((( algorithm python function ) OR ( algorithm 1 function ))) OR ( algorithm basis function ))', query time: 0.47s Refine Results
  1. 141
  2. 142
  3. 143

    Computer Model Emulation with High-Dimensional Functional Output in Large-Scale Observing System Uncertainty Experiments by Pulong Ma (6105767)

    Published 2021
    “…<p>Observing system uncertainty experiments (OSUEs) have been recently proposed as a cost-effective way to perform probabilistic assessment of retrievals for NASA’s Orbiting Carbon Observatory-2 (OCO-2) mission. One important component in the OCO-2 retrieval algorithm is a full-physics forward model that describes the mathematical relationship between atmospheric variables such as carbon dioxide and radiances measured by the remote sensing instrument. …”
  4. 144
  5. 145
  6. 146
  7. 147
  8. 148

    BOFdat: Generating biomass objective functions for genome-scale metabolic models from experimental data by Jean-Christophe Lachance (6619307)

    Published 2019
    “…Despite its importance, no standardized computational platform is currently available to generate species-specific biomass objective functions in a data-driven, unbiased fashion. To fill this gap in the metabolic modeling software ecosystem, we implemented BOFdat, a Python package for the definition of a <b>B</b>iomass <b>O</b>bjective <b>F</b>unction from experimental <b>dat</b>a. …”
  9. 149

    Comparative statistical performance of various algorithms in minimizing the <i>F</i> cost function. by Davut Izci (15927452)

    Published 2023
    “…<p>Comparative statistical performance of various algorithms in minimizing the <i>F</i> cost function.…”
  10. 150

    Bioinformatics pipeline for circadian function. by Patrick B. Schwartz (14782608)

    Published 2023
    “…Concordantly, strong positive correlations (0.5 < ρ < 1, red) should be apparent among transcriptional activators (e.g., <i>BMAL1</i> and <i>CLOCK</i>) and among transcriptional repressors (e.g., <i>NR1D1</i> and <i>PER2</i>), and a strong negative correlation (-0.5 > ρ > -1, blue) should be present amongst activators and repressor targets (e.g., <i>BMAL1</i> and <i>PER2</i>). …”
  11. 151
  12. 152
  13. 153

    Hyperparameter settings of the algorithm 1. by Jin Xu (31283)

    Published 2024
    “…Therefore, this paper presents a novel adaptive control structure for the Twin Delayed Deep Deterministic Policy Gradient algorithm, which is based on a reference trajectory model (TD3-RTM). …”
  14. 154
  15. 155
  16. 156
  17. 157
  18. 158
  19. 159
  20. 160