arXiv (Cornell University)
Graph Drawing via Gradient Descent, $(GD)^2$
August 2020 • Reyan Ahmed, Felice De Luca, Sabin Devkota, Stephen Kobourov, Mingwei Li
Readability criteria, such as distance or neighborhood preservation, are often used to optimize node-link representations of graphs to enable the comprehension of the underlying data. With few exceptions, graph drawing algorithms typically optimize one such criterion, usually at the expense of others. We propose a layout approach, Graph Drawing via Gradient Descent, $(GD)^2$, that can handle multiple readability criteria. $(GD)^2$ can optimize any criterion that can be described by a smooth function. If the criter…