9 citations · 9 across the 9 of their papers we have counts for
5 papers · 1 filter
Word2VecGD: Neural Graph Drawing with Cosine-Stress Optimization
Minglai Yang, Reyan Ahmed
We propose a novel graph visualization method leveraging random walk-based embeddings to replace costly graph-theoretical distance computations. Using word2vec-inspired embeddings,…
Size Should Not Matter: Evaluating Network Visualizations with Stress
Reyan Ahmed, Cesim Erten, Stephen Kobourov +3
The normalized stress metric is widely used to assess graph drawing quality, measuring how closely distances between vertices in a layout match their graph-theoretic distances. Thi…
A Scalable Method for Readable Tree Layouts
Kathryn Gray, Mingwei Li, Reyan Ahmed +4
Large tree structures are ubiquitous and real-world relational datasets often have information associated with nodes (e.g., labels or other attributes) and edges (e.g., weights or…
Splitting Vertices in 2-Layer Graph Drawings
Reyan Ahmed, Patrizio Angelini, Michael A. Bekos +8
Bipartite graphs model the relationships between two disjoint sets of entities in several applications and are naturally drawn as 2-layer graph drawings. In such drawings, the two…
Multicriteria Scalable Graph Drawing via Stochastic Gradient Descent,
Reyan Ahmed, Felice De Luca, Sabin Devkota +2
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 da…