Deep Learning on Graphs

Discover the cutting-edge world of graph neural networks with Deep Learning on Graphs by Yao Ma, published by Cambridge University Press in 2021. This comprehensive hardback edition spans 400 pages, making it an essential resource for students, practitioners, and researchers alike.

This book expertly guides readers from foundational concepts to advanced techniques in graph neural networks. It systematically covers key topics, including filtering, pooling, robustness, and scalability, ensuring a solid understanding of the subject. Furthermore, Deep Learning on Graphs showcases practical applications across various fields such as natural language processing (NLP), data mining, computer vision, and healthcare.

Whether you are looking to deepen your knowledge or apply graph neural networks in real-world scenarios, this book is an invaluable addition to your library. Don't miss the opportunity to enhance your expertise in this rapidly evolving area of science.