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Can I read Deep Learning on Graphs on EtoBox?
Deep Learning on Graphs by Yao Ma, Jiliang Tang is a nonfiction available to read on EtoBox.
What is Deep Learning on Graphs about?
This comprehensive text on the theory and techniques of graph neural networks takes students, practitioners, and researchers from the basics to the state of the art. It systematically introduces foundational topics such as filtering pooling, robustness, and scalability and then demonstrates applications in NLP, data mining, vision and healthcare. Deep learning on graphs has become one of the hottest topics in machine learning. The book consists of four parts to best accommodate our readers with diverse backgrounds and purposes of reading. Part 1 introduces basic concepts of graphs and deep learning; Part 2 discusses the most established methods from the basic to advanced settings; Part 3 presents the most typical applications including natural language processing, computer vision, data mining, biochemistry and healthcare; and Part 4 describes advances of methods and applications that tend to be important and promising for future research. The book is self-contained, making it accessible to a broader range of readers including (1) senior undergraduate and graduate students; (2) practitioners and project managers who want to adopt graph neural networks into their products and platfor
Who reads Deep Learning on Graphs?
It is typically read by self-directed learners exploring a subject in depth.
Common subject areas: history, science, philosophy, social sciences.
- Author
- Yao Ma, Jiliang Tang
- Publisher
- Cambridge University Press (Virtual Publishing)
- Published
- 2021
- Language
- EN
- ISBN
- 9781108924184
- Category
- nonfiction
- Subjects
- Science, Computer Science, Stem