The field of graph representation learning has grown at an incredible (and sometimes unwieldy) pace over the past seven years, transforming from a small subset of researchers working on a relatively niche topic to one of the fastest growing sub-areas of deep learning.

This book is my attempt to provide a brief but comprehensive introduction to graph representation learning, including methods for embedding graph data, graph neural networks, and deep generative models of graphs.

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Contents and Chapter Drafts

Copyrights and Citation

This book is a pre-publication draft of a book that will be published by Morgan & Claypool publishers in late 2020, and the publishers have generously agreed to allow the public hosting of the pre-publication draft. The book should be cited as follows:

William L. Hamilton. (2020). Graph Representation Learning. Morgan & Claypool, forthcoming .

All copyrights held by the author and publishers extend to these pre-publication drafts.

Errata

Feedback, typo corrections, and comments are welcome and should be sent to wlh@cs.mcgill.ca with [GRL BOOK] in the subject line.