Affiliation:
1. School of Computer Science and Technology, Harbin Institute of Technology
Publisher
Institute of Electronics, Information and Communications Engineers (IEICE)
Subject
Artificial Intelligence,Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Hardware and Architecture,Software
Reference14 articles.
1. [1] B. Lee, C. Plaisant, C.S. Parr, J.-D. Fekete, and N. Henry, “Task taxonomy for graph visualization,” Proc. 2006 AVI Workshop on BEyond Time and Errors: Novel Evaluation Methods for Information Visualization, pp.1-5, 2006. 10.1145/1168149.1168168
2. [2] K. Yan and W. Cui, “Visualizing the uncertainty induced by graph layout algorithms,” 2017 IEEE Pacific Visualization Symposium (PacificVis), pp.200-209, IEEE, 2017. 10.1109/pacificvis.2017.8031595
3. [3] Y.Y. Leow, T. Laurent, and X. Bresson, “GraphTSNE: A visualization technique for graph-structured data,” ICLR Workshop on Representation Learning on Graphs and Manifolds, 2019.
4. [4] Y. Wang, Z. Jin, Q. Wang, W. Cui, T. Ma, and H. Qu, “DeepDrawing: A deep learning approach to graph drawing,” IEEE Trans. Vis. Comput. Graph., vol.26, no.1, pp.676-686, 2019. 10.1109/tvcg.2019.2934798
5. [5] X. Wang, K. Yen, Y. Hu, and H.-W. Shen, “DeepGD: A deep learning framework for graph drawing using GNN,” IEEE Comput. Graph. Appl., vol.41, no.5, pp.32-44, 2021. 10.1109/mcg.2021.3093908