Genetic algorithm meta-parameters. by Larasmoyo Nugroho (18078260)

“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”

The entity relationship of DDPG algorithm. by Larasmoyo Nugroho (18078260)

“…<div><p>The PbGA-DDPG algorithm, which uses a potential-based GA-optimized reward shaping function, is a versatiledeep reinforcement learning/DRLagent that can control a vehicle in a complex environment without prior knowledge. …”

Pairwise alignment results from human proteins and <i>H</i>. <i>pylori</i> proteins using Blosum 62 and PM250 algorithms. by Andrés Sánchez Caraballo (15354081)

Reconstruction performance across algorithms, dynamics, cell types, and recording length. by Christian Donner (3663007)

“…<b>D</b> The mean average precision score (APS, upper panel) and Matthews correlation coefficient (MCC, lower panel), estimated across all connections, obtained from all inference algorithms and the eANN across three different dynamical regimes. …”

MSIPOA algorithm flow chart. by Chuang Zhang (2199421)

“…A levy flight strategy further improves the algorithm’s ability to jump out of local minima. In this paper, 12 benchmark test functions and 8 other newer swarm intelligence algorithms are compared in terms of convergence speed and convergence accuracy to evaluate the performance of the MSIPOA algorithm. …”

As for Fig 2, we present failure rates as a function of the cohort size (vertical axis) versus the number of distractors (horizontal axis), for the Smyth and McClave baseline algorithm from [76]. by Daniela Huppenkothen (9174507)

“…We note that the middle row is a special case: here, <i>f</i>_target only corresponds to the proportions of the embedded cohort, while “success” for these two panels is defined as recovering maximally diverse cohorts, as this particular algorithm is designed to do. The bottom row shows the same simulations as the middle row, but presents successes and failures when the targets that generated the embedded cohort are applied instead of the balanced targets that are part of the baseline’s objective function. …”

Top 15 hub genes in five algorithms. by Tianqi Liu (1625776)

Parameter setting. by Peiying Li (797714)

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S1 File - by Peiying Li (797714)

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Structure diagram of fuzzy controller. by Peiying Li (797714)

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Improved A* flowchart. by Peiying Li (797714)

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Schematic diagram of optimizing sub nodes. by Peiying Li (797714)

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Basic structure of extended revolutionary kernel. by Peiying Li (797714)

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Venn diagrams showing overlap of the total of overrepresented/underrepresented kinases for both cohorts. by Erica A. K. DePasquale (11851483)

The visual quality performance comparison of the enhanced image obtained by various image enhancement approaches. by Xiaowen Zhang (83669)

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Visual quality performance comparison of the enhanced image obtained by various image enhancement approaches. by Xiaowen Zhang (83669)

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Increasing consensus of context-specific metabolic models by integrating data-inferred cell functions by Anne Richelle (6589178)

“…Models can quantify the activities of diverse pathways and cellular functions. Since some metabolic reactions are only catalyzed in specific environments, several algorithms exist that build context-specific models. …”

PyNoetic’s online mode in action. Data is streamed from an Emotiv EPOC headset. by Gursimran Singh (575288)

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Construction of internuclear persistence contours (IPCs). by Yuxi Long (11024307)

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An overview of PATH⁺. by Yuxi Long (11024307)

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