<
From version < 7.1 >
edited by Alexander Schulz-Rosengarten
on 2022/10/06 10:03
To version < 8.1 >
edited by Maximilian Kasperowski
on 2022/10/06 11:44
>
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Author
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1 -XWiki.als
1 +XWiki.mka
Content
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1 -TODO Satz zu top-down
1 +Top-down Layout is a technique to draw large hierarchical diagrams from the root node downwards, scaling children down to fit in the space provided by their parents. This is in contrast to bottom-up layout where children are laid out first and the parents' dimensions are determined accordingly afterwards.
2 2  
3 3  In top-down layout a strategy needs to be used to set node sizes without knowledge of the hierarchical contents of the node as that has not been processed/laid out at that point. Current strategies are:
4 4  
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28 28  
29 29  = Related Work/Literature =
30 30  
31 -[WIP] Top-down layout paper
31 +[Under Review] M. Kasperowski and R. von Hanxleden, //Top-down Layout: Utilizing Zoom as the Third Dimension//
32 32  
33 -[[http:~~/~~/neuralnetworksanddeeplearning.com/index.html>>url:http://neuralnetworksanddeeplearning.com/index.html||shape="rect"]]
33 +M. Nielsen, //Neural Networks and Deep Learning//, Determination Press, 2015 ([[http:~~/~~/neuralnetworksanddeeplearning.com/index.html>>url:http://neuralnetworksanddeeplearning.com/index.html||shape="rect"]])
34 34  
35 -[[https:~~/~~/www.deeplearningbook.org/>>url:https://www.deeplearningbook.org/||shape="rect"]]
35 +I. Goodfellow and Y. Bengio and A. Courville, //Deep Learning//, MIT Press, 2016 ([[https:~~/~~/www.deeplearningbook.org/>>url:https://www.deeplearningbook.org/||shape="rect"]])
36 36  
37 37  = Involved Languages/Technologies =
38 38  
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44 44  
45 45  Maximilian Kasperowski
46 46  
47 -mka@
47 +mka@informatik.uni-kiel.de
Confluence.Code.ConfluencePageClass[0]
Id
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1 -136183951
1 +136183954
URL
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1 -https://rtsys.informatik.uni-kiel.de/confluence//wiki/spaces/RTSYS/pages/136183951/A Machine Learning Approach for Node Size Approximation in Top-down Layout
1 +https://rtsys.informatik.uni-kiel.de/confluence//wiki/spaces/RTSYS/pages/136183954/A Machine Learning Approach for Node Size Approximation in Top-down Layout