Graph neural networks are intimately related to partial differential equations governing information diffusion on graphs. Thinking of GNNs as PDEs leads to a new broad class of graph ML methods.
Fullstack GraphQL Tutorial to go from zero to production covering all basics and advanced concepts. Includes tutorials for Apollo, Relay, React and NodeJS.
W. Hamilton, R. Ying, и J. Leskovec. (2017)cite arxiv:1709.05584Comment: Published in the IEEE Data Engineering Bulletin, September 2017; version with minor corrections.