Search alternatives:
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
lead optimization » global optimization (Expand Search), swarm optimization (Expand Search), whale optimization (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
function optimization » reaction optimization (Expand Search), formulation optimization (Expand Search), generation optimization (Expand Search)
lead optimization » global optimization (Expand Search), swarm optimization (Expand Search), whale optimization (Expand Search)
based function » based functional (Expand Search), basis function (Expand Search), basis functions (Expand Search)
binary based » library based (Expand Search), linac based (Expand Search), binary mask (Expand Search)
less based » lens based (Expand Search), lemos based (Expand Search), degs based (Expand Search)
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<i>hi</i>PRS algorithm process flow.
Published 2023“…From this dataset we can compute the MI between each interaction and the outcome and <b>(D)</b> obtain a ranked list (<i>I</i><sub><i>δ</i></sub>) based on this metric. <b>(E)</b> Starting from the interaction at the top of <i>I</i><sub><i>δ</i></sub>, <i>hi</i>PRS constructs <i>I</i><sub><i>K</i></sub>, selecting <i>K</i> (where <i>K</i> is user-specified) terms through the greedy optimization of the ratio between MI (<i>relevance</i>) and a suitable measure of similarity for interactions (<i>redundancy)</i> (cf. …”
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Genetic algorithm meta-parameters.
Published 2024“…<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. …”
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The entity relationship of DDPG algorithm.
Published 2024“…<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. …”
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Decoding evidence for feature triplets on test tasks.
Published 2025“…<p>Another neural hypothesis formulated based on the SF&GPI algorithm is that feature triplets associated with the optimal training policies should be reactivated on test trials. …”
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Codes for high-order analytical continuation algorithms based on direct derivation and recursion methods
Published 2024“…The optimal order of the analytical continuation algorithm is contingent upon the noise level of gravity data. …”
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Performance comparison of four optimization methods.
Published 2025“…(B) Relative error convergence of four optimization methods, plotted as a function of the logarithm of iterations. …”
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SBH17: Benchmark Database of Barrier Heights for Dissociative Chemisorption on Transition Metal Surfaces
Published 2022“…The medium algorithm does require metal lattice constants and interlayer distances that are optimized separately for each functional. …”
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Supporting data for "Two Essays on Consumers' Relative Preference for Algorithm-based Versus Human Recommendations"
Published 2023“…<p>Recommendation systems, the information filtering tools that provide options of products or services to customers, are powered by programmed algorithms or human experts. Both algorithm-based and human recommendation systems are widely adopted by companies to help consumers make optimal purchasing decisions amid their access to product information. …”
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Process of generating MS/MS spectra from a protein mixture using mass-spectrometry analysis.
Published 2021Subjects: -
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2D UMAP visualization of embedded spectra and peptide vectors generated by SpeCollate.
Published 2021Subjects: -
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