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Deep Learning Graphs by Yao Tang (17 results)
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: New.
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
Seller: Ria Christie Collections, Uxbridge, United Kingdom
Seller rating 5 out of 5 stars
Condition: New. In.
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
Seller: GreatBookPricesUK, Woodford Green, United Kingdom
Seller rating 5 out of 5 stars
Condition: As New. Unread book in perfect condition.
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
Hardcover. Condition: Brand New. 400 pages. 9.25x6.18x0.91 inches. In Stock.
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Deep Learning on Graphs
Published by Cambridge University Press (edition 1), 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 60
Convert currency£ 4.47 shipping from U.S.A. to United KingdomQuantity: 2 available
Add to basketHardcover. Condition: Very Good. 1. Ship within 24hrs. Satisfaction 100% guaranteed. APO/FPO addresses supported.
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
Condition: New.
-
Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 59.22
Convert currency£ 7.47 shipping from U.S.A. to United KingdomQuantity: 10 available
Add to basketCondition: New.
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 51.81
Convert currency£ 14.93 shipping from U.S.A. to United KingdomQuantity: Over 20 available
Add to basketCondition: New.
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Deep Learning on Graphs
Published by Cambridge University Press, GB, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
Hardback. Condition: New. 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 platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 57.26
Convert currency£ 14.93 shipping from U.S.A. to United KingdomQuantity: 1 available
Add to basketCondition: As New. Unread book in perfect condition.
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Deep Learning on Graphs
Published by Cambridge University Press, GB, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 73.48
Convert currencyFree shipping from U.S.A. to United KingdomQuantity: 2 available
Add to basketHardback. Condition: New. 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 platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.
-
Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 74.07
Convert currency£ 6.89 shipping from Germany to United KingdomQuantity: 3 available
Add to basketCondition: New.
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 61.25
Convert currency£ 21.66 shipping from Germany to United KingdomQuantity: 4 available
Add to basketCondition: New. 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.
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Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
Hardcover. Condition: Brand New. 400 pages. 9.25x6.18x0.91 inches. In Stock.
-
Deep Learning on Graphs
Published by Cambridge University Press, GB, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
Seller: Rarewaves.com USA, London, LONDO, United Kingdom
Seller rating 4 out of 5 stars
Hardback. Condition: New. 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 platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.
-
Deep Learning on Graphs
Published by Cambridge University Press, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 52.74
Convert currency£ 56 shipping from U.S.A. to United KingdomQuantity: 3 available
Add to basketCondition: New.
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Deep Learning on Graphs
Published by Cambridge University Press, GB, 2021
ISBN 10: 1108831745 ISBN 13: 9781108831741
Language: English
£ 74.51
Convert currency£ 85.87 shipping from U.S.A. to United KingdomQuantity: 2 available
Add to basketHardback. Condition: New. 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 platforms; and (3) researchers without a computer science background who want to use graph neural networks to advance their disciplines.
