Showing 41 - 60 results of 17,108 for search '(((( algorithm i function ) OR ( algorithm system function ))) OR ( algorithm python function ))*', query time: 1.49s Refine Results
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    <b>Opti2Phase</b>: Python scripts for two-stage focal reducer by Morgan Najera (21540776)

    Published 2025
    “…</li></ul><p dir="ltr">The scripts rely on the following Python packages. Where available, repository links are provided:</p><ol><li><b>NumPy</b>, version 1.22.1</li><li><b>SciPy</b>, version 1.7.3</li><li><b>PyGAD</b>, version 3.0.1 — https://pygad.readthedocs.io/en/latest/#</li><li><b>bees-algorithm</b>, version 1.0.2 — https://pypi.org/project/bees-algorithm</li><li><b>KrakenOS</b>, version 1.0.0.19 — https://github.com/Garchupiter/Kraken-Optical-Simulator</li><li><b>matplotlib</b>, version 3.5.2</li></ol><p dir="ltr">All scripts are modular and organized to reflect the design stages described in the manuscript.…”
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    ADT: A Generalized Algorithm and Program for Beyond Born–Oppenheimer Equations of “<i>N</i>” Dimensional Sub-Hilbert Space by Koushik Naskar (7510592)

    Published 2020
    “…For the numerical case, user can directly provide <i>ab initio</i> data (adiabatic PESs and NACTs) as input files to this software or can generate those input files through in-built python codes interfacing MOLPRO followed by ADT calculation. …”
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    Efficient algorithms to discover alterations with complementary functional association in cancer by Rebecca Sarto Basso (6728921)

    Published 2019
    “…We provide analytic evidence of the effectiveness of UNCOVER in finding high-quality solutions and show experimentally that UNCOVER finds sets of alterations significantly associated with functional targets in a variety of scenarios. In particular, we show that our algorithms find sets which are better than the ones obtained by the state-of-the-art method, even when sets are evaluated using the statistical score employed by the latter. …”
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    <i>K</i>-CDFs: A Nonparametric Clustering Algorithm via Cumulative Distribution Function by Jicai Liu (11419050)

    Published 2022
    “…<p>We propose a novel partitioning clustering procedure based on the cumulative distribution function (CDF), called <i>K</i>-CDFs. For univariate data, the <i>K</i>-CDFs represent the cluster centers by empirical CDFs and assign each observation to the closest center measured by the Cram<math><mrow><mi>e</mi><mo>´</mo></mrow></math>r-von Mises distance. …”
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    S1 File - by Yuh-Chin T. Huang (17867207)

    Published 2024
    Subjects:
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