Scientific data-sets often come with an inherent hierarchical structure such as functional substructures within organs. In this work we propose a new visualization approach for vo...
Jean-Paul Balabanian, Ivan Viola, Martin Ystad, Ar...
In genetic programming (GP), evolving tree nodes separately would reduce the huge solution space. However, tree nodes are highly interdependent with respect to their fitness. In th...
Gang Li, Jin Feng Wang, Kin-Hong Lee, Kwong-Sak Le...
We present a latent hierarchical structural learning method for object detection. An object is represented by a mixture of hierarchical tree models where the nodes represent objec...
Leo Zhu, Yuanhao Chen, Antonio Torralba, Alan Yuil...
This paper is motivated by some recent, intriguing research results involving agent-organized networks (AONs). In AONs, nodes represent agents, and collaboration between nodes are...
We present the H3 layout technique for drawing large directed graphs as node-link diagrams in 3D hyperbolic space. We can lay out much larger structures than can be handled using ...