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algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
algorithm fibrin » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm from (توسيع البحث)
python function » protein function (توسيع البحث)
fibrin function » brain function (توسيع البحث)
algorithm a » algorithm _ (توسيع البحث), algorithm b (توسيع البحث), algorithms _ (توسيع البحث)
a function » _ function (توسيع البحث)
algorithm python » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm both (توسيع البحث)
algorithm fibrin » algorithm within (توسيع البحث), algorithms within (توسيع البحث), algorithm from (توسيع البحث)
python function » protein function (توسيع البحث)
fibrin function » brain function (توسيع البحث)
algorithm a » algorithm _ (توسيع البحث), algorithm b (توسيع البحث), algorithms _ (توسيع البحث)
a function » _ function (توسيع البحث)
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BioJupiter interface and functionalities.pdf
منشور في 2022"…BioJupiter interface and functionalities. (a-c) The application interface. (a) main heatmap, (b) the main alignment result, (c) the local storage browser and disk operations. …"
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Network Gradient Descent Algorithm for Decentralized Federated Learning
منشور في 2022"…<p>We study a fully decentralized federated learning algorithm, which is a novel gradient descent algorithm executed on a communication-based network. …"
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Swarm intelligence algorithms for width and length on influence games
منشور في 2021"…<br><br><div>usage: Main.py [-h] [-a] [-r] [-d D] [-t T] [-i I] [-q Q] [--shape SHAPE] [--sym] [--folder FOLDER] [--seed SEED] [--sum SUM] [--mh MH] [--tagsfile TAGSFILE] [--notags] [--prune] [--excludenodes EXCLUDENODES]<br><br>Calculates the best Influence Spread set on a Weighted Symmetric Graph using PSO<br></div><div><br></div><div><div>positional arguments:</div><div> file</div><div><br></div><div>optional arguments:</div><div> -h, --help: show this help message and exit</div><div> -a: threat file input contents as an Adjacency Matrix</div><div> -r: reverse order of nodes, from (a,b,w) a -> b will be b -> a</div><div> -d D: line separator to use while parsing</div><div> -t T: number of times to execute</div><div> -i I: number of metaheuristic iterations per execution</div><div> -q Q: fixed quota, use 0 = floor(n/2)+1</div><div> --shape SHAPE: shape functions for binarization - list of implemented shape functions: s2,s2_neg,v2,v4</div><div> --sym: consider graph as symmetric instead of directed</div><div> --folder FOLDER: output folder</div><div> --seed SEED: use custom seed for metaheuristic calcs</div><div> --sum SUM: adds a value to all node labels</div><div> --mh MH: metaheuristic to use - list of implemented metaheuristics: {1: 'Swarm', 2: 'Swarm2', 3: 'Swarm_W', 4:</div><div> 'Swarm_L'}</div><div> --tagsfile TAGSFILE: use first row as node tags instead of using plurality criteria</div><div> --notags: do not use first row as node tags - tags will be calculated</div><div> --prune: nodes with outdegree = 0 and indegree > 0, and with outdegree = 1 and neighbor's outdegree > 0 will be excluded</div><div> --excludenodes EXCLUDENODES: nodes to skip, comma separated</div></div>…"
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Algorithms for continuous and discrete abelian groups and their related classes
منشور في 2024"…The algorithms are implemented and published as a collection of GAP4 functions named <b>codiaga</b> (see Ö. …"
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