15 citations · 79 across the 25 of their papers we have counts for
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cs.CV2020★ 1 cited
Distance-Geometric Graph Convolutional Network (DG-GCN) for Three-Dimensional (3D) Graphs
Daniel T. Chang
The distance-geometric graph representation adopts a unified scheme (distance) for representing the geometry of three-dimensional(3D) graphs. It is invariant to rotation and transl…
cs.CV2020★ 1 cited
Geometric Graph Representations and Geometric Graph Convolutions for Deep Learning on Three-Dimensional (3D) Graphs
Daniel T. Chang
The geometry of three-dimensional (3D) graphs, consisting of nodes and edges, plays a crucial role in many important applications. An excellent example is molecular graphs, whose g…