Kruiger, J. F.Rauber, Paulo E.Martins, Rafael MessiasKerren, AndreasKobourov, StephenTelea, Alexandru C.Heer, Jeffrey and Ropinski, Timo and van Wijk, Jarke2017-06-122017-06-1220171467-8659https://doi.org/10.1111/cgf.13187https://diglib.eg.org:443/handle/10.1111/cgf13187We propose a new graph layout method based on a modification of the t-distributed Stochastic Neighbor Embedding (t-SNE) dimensionality reduction technique. Although t-SNE is one of the best techniques for visualizing high-dimensional data as 2D scatterplots, t-SNE has not been used in the context of classical graph layout. We propose a new graph layout method, tsNET, based on representing a graph with a distance matrix, which together with a modified t-SNE cost function results in desirable layouts. We evaluate our method by a formal comparison with state-of-the-art methods, both visually and via established quality metrics on a comprehensive benchmark, containing real-world and synthetic graphs. As evidenced by the quality metrics and visual inspection, tsNET produces excellent layouts.10.1111/cgf.13187283-294