Contents |
We are going to review a series of seminal papers (2019-2022) that have been building up for the basic concepts and algorithms for the Self-Supervised Learning on graph neural networks which is now one of the hottest research area in A.I. We start with "SimCLR(ICML 2020)" continue to cover "CPC(2018,arXiv, in progress)," BYOL(NeurIPS 2020)", "GraphCL(NeurIPS2020), "CMVRL(ICML2020)", PPNP&APPNP(ICLR 2019), and "GRAND(ICML2021)" including MarkovGNN(WWW2022 Companion)". These papers are going to suggest many funddamental questions about SSL on graphs which cloud be reduced to the frameworks of Graph Theory, Algebra, Topology, Geometry and Analysis along with Probability and Statistics. |