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From the 1 of 14 linked papers with an AI index.

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14 papers

cs.CG2026

Minimum-Width Drawing of Trees with Sized Vertices

Markus Wallinger, Oscar Navarro, Stephen G. Kobourov

The paper studies how to reorder the children of each node in a rooted tree with given vertex sizes to minimize the width of a layered drawing, proving the problem NP‑complete and…

cs.CV2026

3DMPE: 3D Multi-Perspective Embedding

Vahan Huroyan, Md Rahat-uz-Zaman, Stephen Kobourov

We study 3D point cloud reconstruction from multiple partially observed 2D projections. Given two or more projections of an unknown 3D point cloud, together with cross-view point c…

cs.LG2026

Visualizing High-Dimensional Graph Embeddings via Informed Multi-View Projections

Ya Ji, Xuefeng Li, Timo Brand +4

Graphs are commonly visualized in 2D, where humans readily interpret spatial relationships, yet such layouts often distort higher-dimensional structure. We propose to embed graphs…

cs.CG2026

Using Reinforcement Learning to Optimize the Global and Local Crossing Number

Timo Brand, Henry Förster, Henry Förster +5

Graph drawing concerns the algorithmic visualization of graphs. A good drawing of a graph is easy to read and facilitates solving tasks on the graph. Several properties have been i…

cs.CG2026

Representing Hypergraphs by Point-Line Incidences

Alexander Dobler, Stephen Kobourov, Debajyoti Mondal +1

We consider hypergraph visualizations that represent vertices as points in the plane and hyperedges as curves passing through the points of their incident vertices. Specifically, w…

cs.LG2026

Bridging Graph Drawing and Dimensionality Reduction with Stochastic Stress Optimization

Daniel Hangan, Stephen Kobourov, Jacob Miller

Both Dimensionality Reduction (DR) and Graph Drawing (GD) aim to visualize abstract, non-linear structures, yet rely on different optimization paradigms. This contrast is evident i…