A complete guide to graph representation learning with case studies /
"This book provides a concise understanding of the subject of graph representation learning (GRL) which is a rapidly advancing field in the domain of machine learning. It includes such aspects as the basic concepts, state-of-the-art techniques, and real world applications of GRL which enable th...
| Main Authors: | , , |
|---|---|
| Format: | eBook |
| Language: | English |
| Published: |
Hoboken, New Jersey :
John Wiley & Sons, Inc.,
[2026]
|
| Subjects: | |
| Online Access: | Connect to the full text of this electronic book |
| Summary: | "This book provides a concise understanding of the subject of graph representation learning (GRL) which is a rapidly advancing field in the domain of machine learning. It includes such aspects as the basic concepts, state-of-the-art techniques, and real world applications of GRL which enable the reader to progress from a fundamental understanding of the approach to mastering its application. The authors also cover the topics of graph embedding methods, graph neural network (GNN) -based approaches and the latest trends in GRL such as deep learning, transfer learning, graph pooling, alignment, matching and graph machine learning. The book also includes examples of real-world applications of graph learning methods with real-world case studies in which the presented methods can be utilized"-- Provided by publisher. |
|---|---|
| Physical Description: | 1 online resource |
| ISBN: | 9781394314874 1394314876 9781394314881 1394314884 |