DeepFD: a deep learning approach to fast generate force-directed layout for large graphs
Author:
Funder
National Natural Science Foundation of China
Publisher
Springer Science and Business Media LLC
Link
https://link.springer.com/content/pdf/10.1007/s12650-024-00991-1.pdf
Reference41 articles.
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2. Barnes J, Hut P (1986) A hierarchical o (n log n) force-calculation algorithm. Nature 324(6096):446–449
3. Belkin M, Niyogi P (2003) Laplacian eigenmaps for dimensionality reduction and data representation. Neural Comput 15(6):1373–1396. https://doi.org/10.1162/089976603321780317
4. Brandes U, Pich C (2007) Eigensolver methods for progressive multidimensional scaling of large data. In: Kaufmann M, Wagner D (eds) Graph drawing. Springer, Berlin, pp 42–53
5. Cohen JD (1997) Drawing graphs to convey proximity: an incremental arrangement method. ACM Trans Comput Hum Interact 4(3):197–229. https://doi.org/10.1145/264645.264657
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