Deep Learning has been a subject of interest in solving a lot of complex machine learning problems, more recently on graph data. However most of the solutions are either supervised or semi-supervised which rely highly on labels in the data, causing over-fitting and overall weak robustness. Self-Supervised Learning (SSL) is an up-and-coming solution which mines useful information from unlabelled data making it a very interesting choice in the field of graph data.
SSL helps in understanding structural and attributive information that is present in the graph data which would otherwise be ignored when labelled data is used
Getting labelled graph…
Data Science at SJSU