Graph Neural Networks: A Review of Methods and Applications

Graph Neural Networks: A Review of Methods and Applications

Lots of learning tasks require dealing with graph data which contains rich relation information a...概要を表示 Lots of learning tasks require dealing with graph data which contains rich relation information among elements. Modeling physics systems, learning molecular fingerprints, predicting protein interface, and classifying diseases demand a model to learn from graph inputs. In other domains such as learning from non-structural data like texts and images, reasoning on extracted structures (like the depen