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algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
algorithm steps » algorithm shows (Expand Search), algorithm models (Expand Search)
python function » protein function (Expand Search)
where function » sphere function (Expand Search), gene function (Expand Search), wave function (Expand Search)
steps function » step function (Expand Search), its function (Expand Search), cep function (Expand Search)
algorithm python » algorithm within (Expand Search), algorithms within (Expand Search), algorithm both (Expand Search)
algorithm steps » algorithm shows (Expand Search), algorithm models (Expand Search)
python function » protein function (Expand Search)
where function » sphere function (Expand Search), gene function (Expand Search), wave function (Expand Search)
steps function » step function (Expand Search), its function (Expand Search), cep function (Expand Search)
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Bioinformatics pipeline for circadian function.
Published 2023“…CYCLOPS (cyclic ordering by periodic structure) is an algorithm that can identify rhythmic (longitudinal) data from population data where sample time acquisition is unknown. …”
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843
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Flow Φ of the controlled continuous time PDMP.
Published 2024“…We propose modeling cancer evolution using a Piecewise Deterministic Markov Process, where patients alternate between remission and relapse phases, and control the model via long-term cost function optimization. …”
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845
DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf
Published 2023“…Superiorization combines a feasibility-seeking projection algorithm with objective function reduction: The underlying projection algorithm is perturbed with gradient descent steps to steer the algorithm towards a solution with a lower objective function value compared to one obtained solely through feasibility-seeking.…”
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846
DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf
Published 2023“…Superiorization combines a feasibility-seeking projection algorithm with objective function reduction: The underlying projection algorithm is perturbed with gradient descent steps to steer the algorithm towards a solution with a lower objective function value compared to one obtained solely through feasibility-seeking.…”
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847
DataSheet_1_Superiorization of projection algorithms for linearly constrained inverse radiotherapy treatment planning.pdf
Published 2023“…Superiorization combines a feasibility-seeking projection algorithm with objective function reduction: The underlying projection algorithm is perturbed with gradient descent steps to steer the algorithm towards a solution with a lower objective function value compared to one obtained solely through feasibility-seeking.…”
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Image_1_KairoSight: Open-Source Software for the Analysis of Cardiac Optical Data Collected From Multiple Species.TIF
Published 2021“…Despite the refinement of software tools and algorithms, significant programming expertise is often required to analyze large optical data sets, and data analysis can be laborious and time-consuming. …”
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850
Data_Sheet_1_Modeling the development of cortical responses in primate dorsal (“where”) pathway to optic flow using hierarchical neural field models.PDF
Published 2023“…On the other hand, model-3 consists of the Velocity Selective Mosaic Network (VSMN) followed by a convolutional neural network (CNN) which is trained on radial and rotational sequences using a supervised backpropagation algorithm. The quantitative comparison of response similarity matrices (RSMs), made out of convolution layer and last hidden layer responses, show that model-3 neuron responses are consistent with the idea of functional hierarchy in the macaque motion pathway. …”
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An illustrating example of solving the WTA problem.avi
Published 2019“…For target 1, the damage probabilities P<sub>i1</sub> of each weapon are {0.4401, 0.0482, 0.2900, 0.1189, 0.0557, 0.1641, 0.7665}; for target 2, the damage probabilities P<sub>i2</sub> of each weapon are {0.3824, 0.0802, 0.3017, 0.7488, 0.1476, 0.3024, 0.1002}; for target 3, the damage probabilities P<sub>i3</sub> of each weapon are {0.0918, 0.2039, 0.1156, 0.2832, 0.5620, 0.2048, 0.0407}, where i=1,2,…,7.</div><div><br></div><div>Each weapon simulator implements the hybrid algorithm that combines the redesigned auction algorithm (Stage 1) and the improved task swap algorithm (Stage 2) in a decentralized manner. …”
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Top 20 hub genes identified in non-preserved module based on module intraconnectivity.
Published 2024Subjects: -
856
The relationship of Soft Threshold (power) with Scale Free Topology (A) and Mean Connectivity (B).
Published 2024Subjects: -
857
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