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phase function » phase functions (Expand Search), sphere function (Expand Search), rate function (Expand Search)
algorithm setup » algorithm seu (Expand Search), algorithm steps (Expand Search), algorithm etc (Expand Search)
algorithm phase » algorithm based (Expand Search), algorithm where (Expand Search), algorithm pre (Expand Search)
within function » fibrin function (Expand Search), python function (Expand Search), protein function (Expand Search)
setup function » step function (Expand Search), t4p function (Expand Search), cep function (Expand Search)
phase function » phase functions (Expand Search), sphere function (Expand Search), rate function (Expand Search)
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<b>Opti2Phase</b>: Python scripts for two-stage focal reducer
Published 2025“…<p dir="ltr"><b>Opti2Phase: Python Scripts for Two-Stage Focal Reducer Design</b></p><p dir="ltr">The folder <b>Opti2Phase</b> contains the Python scripts used to generate the results presented in the manuscript. …”
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TV-BayesOpt algorithm performance for tracking a gradual drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*.
Published 2023“…For each estimated GPR the confidence bounds observed at the predicted optimal phase value are small and become larger for values further away from this value due to the algorithm’s acquisition function prioritizing exploitation of the parameter space during the optimization process.…”
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TV-BayesOpt algorithm performance for tracking a periodic drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*.
Published 2023“…For each estimated GPR the confidence bounds observed at the predicted optimal phase value are small and become larger for values further away from this value due to the algorithm’s acquisition function prioritizing exploitation of the parameter space during the optimization process.…”
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TV-BayesOpt algorithm performance for tracking a superimposed (gradual and periodic) drift in the optimal stimulation phase for phase-locked stimulation, <i>ψ</i>*.
Published 2023“…For each estimated GPR the confidence bounds observed at the predicted optimal phase value are small and become larger for values further away from this value due to the algorithm’s acquisition function prioritizing exploitation of the parameter space during the optimization process.…”
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Taming Negative Ion Resonances Using Nonlocal Exchange-Correlation Functionals
Published 2024Subjects: -
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