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Cover: 9781108831741 | Deep Learning on Graphs | Yao Ma (u. a.) | Buch | Gebunden | Englisch
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Deep Learning on Graphs
Buch von Jiliang Tang (u. a.)
Sprache: Englisch

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Beschreibung
A comprehensive text on foundations and techniques of graph neural networks with applications in NLP, data mining, vision and healthcare.
A comprehensive text on foundations and techniques of graph neural networks with applications in NLP, data mining, vision and healthcare.
Über den Autor
Yao Ma is a PhD student of the Department of Computer Science and Engineering at Michigan State University (MSU). He is the recipient of the Outstanding Graduate Student Award and FAST Fellowship at MSU. He has published papers in top conferences such as WSDM, ICDM, SDM, WWW, IJCAI, SIGIR and KDD, which have been cited hundreds of times. He is the leading organizer and presenter of tutorials on GNNs at AAAI'20, KDD'20 and AAAI'21, which received huge attention and wide acclaim. He has served as Program Committee Members/Reviewers in many well-known conferences and magazines such as AAAI, BigData, IJCAI, TWEB, TKDD and TPAMI.
Inhaltsverzeichnis
1. Deep Learning on Graphs: An Introduction; 2. Foundation of Graphs; 3. Foundation of Deep Learning; 4. Graph Embedding; 5. Graph Neural Networks; 6. Robust Graph Neural Networks; 7. Scalable Graph Neural Networks; 8. Graph Neural Networks for Complex Graphs; 9. Beyond GNNs: More Deep Models for Graphs; 10. Graph Neural Networks in Natural Language Processing; 11. Graph Neural Networks in Computer Vision; 12. Graph Neural Networks in Data Mining; 13. Graph Neural Networks in Biochemistry and Healthcare; 14. Advanced Topics in Graph Neural Networks; 15. Advanced Applications in Graph Neural Networks.
Details
Erscheinungsjahr: 2021
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108831741
ISBN-10: 1108831745
Sprache: Englisch
Einband: Gebunden
Autor: Tang, Jiliang
Ma, Yao
Hersteller: Cambridge University Press
Maße: 330 x 264 x 2 mm
Von/Mit: Jiliang Tang (u. a.)
Erscheinungsdatum: 23.09.2021
Gewicht: 0,594 kg
Artikel-ID: 120325596
Über den Autor
Yao Ma is a PhD student of the Department of Computer Science and Engineering at Michigan State University (MSU). He is the recipient of the Outstanding Graduate Student Award and FAST Fellowship at MSU. He has published papers in top conferences such as WSDM, ICDM, SDM, WWW, IJCAI, SIGIR and KDD, which have been cited hundreds of times. He is the leading organizer and presenter of tutorials on GNNs at AAAI'20, KDD'20 and AAAI'21, which received huge attention and wide acclaim. He has served as Program Committee Members/Reviewers in many well-known conferences and magazines such as AAAI, BigData, IJCAI, TWEB, TKDD and TPAMI.
Inhaltsverzeichnis
1. Deep Learning on Graphs: An Introduction; 2. Foundation of Graphs; 3. Foundation of Deep Learning; 4. Graph Embedding; 5. Graph Neural Networks; 6. Robust Graph Neural Networks; 7. Scalable Graph Neural Networks; 8. Graph Neural Networks for Complex Graphs; 9. Beyond GNNs: More Deep Models for Graphs; 10. Graph Neural Networks in Natural Language Processing; 11. Graph Neural Networks in Computer Vision; 12. Graph Neural Networks in Data Mining; 13. Graph Neural Networks in Biochemistry and Healthcare; 14. Advanced Topics in Graph Neural Networks; 15. Advanced Applications in Graph Neural Networks.
Details
Erscheinungsjahr: 2021
Genre: Informatik
Rubrik: Naturwissenschaften & Technik
Medium: Buch
Inhalt: Gebunden
ISBN-13: 9781108831741
ISBN-10: 1108831745
Sprache: Englisch
Einband: Gebunden
Autor: Tang, Jiliang
Ma, Yao
Hersteller: Cambridge University Press
Maße: 330 x 264 x 2 mm
Von/Mit: Jiliang Tang (u. a.)
Erscheinungsdatum: 23.09.2021
Gewicht: 0,594 kg
Artikel-ID: 120325596
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