Why Graph Neural Networks Are Gaining Popularity In 2021

Graph Neural Networks (GNNs) is a subtype of neural networks that operate on data structured as graphs. In an article covered earlier on Geometric Deep Learning, we saw how image processing, image classification, and speech recognition are represented in the Euclidean space. Graphs are non-Euclidean and can be used to study and analyse 3D data. GNN involves converting non-structured data like images and text into graphs to perform analysis. A graph is usually a representation of a data structure with two components -- Vertices (V) and Edges (E), which is generally put as; G Ω (V, E).