000			01480nam a22001817a 4500
005			20250502115812.0
008			250502b2021 |||||||| |||| 00| 0 eng d
020			_a9781108831741
082			_a006.31 M-YAO
100			_aMa, Yao
245			_aDeep learning on graphs / _cYao Ma and Jiliang Tang
260			_aIndia _bCambridge University Press _c2021
300			_a320p.
500			_aDeep 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 platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines
650			_aMachine learning
650			_aGraph algorithms
650			_aDeep learning (Machine learning)
999			_c93474 _d93474