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標題: Titlebook: Introduction to Graph Neural Networks; Zhiyuan Liu,Jie Zhou Book 2020 Springer Nature Switzerland AG 2020 [打印本頁]

作者: 皺紋    時間: 2025-3-21 19:34
書目名稱Introduction to Graph Neural Networks影響因子(影響力)




書目名稱Introduction to Graph Neural Networks影響因子(影響力)學科排名




書目名稱Introduction to Graph Neural Networks網(wǎng)絡公開度




書目名稱Introduction to Graph Neural Networks網(wǎng)絡公開度學科排名




書目名稱Introduction to Graph Neural Networks被引頻次




書目名稱Introduction to Graph Neural Networks被引頻次學科排名




書目名稱Introduction to Graph Neural Networks年度引用




書目名稱Introduction to Graph Neural Networks年度引用學科排名




書目名稱Introduction to Graph Neural Networks讀者反饋




書目名稱Introduction to Graph Neural Networks讀者反饋學科排名





作者: Repatriate    時間: 2025-3-21 22:15

作者: 糾纏    時間: 2025-3-22 03:36
Introduction to Graph Neural Networks978-3-031-01587-8Series ISSN 1939-4608 Series E-ISSN 1939-4616
作者: 捕鯨魚叉    時間: 2025-3-22 07:53
Vanilla Graph Neural Networks,In this section, we describe the vanilla GNNs proposed in Scarselli et al. [2009]. We also list the limitations of the vanilla GNN in representation capability and training efficiency. After this chapter we will talk about several variants ofthe vanilla GNN model.
作者: 催眠    時間: 2025-3-22 10:05

作者: Assignment    時間: 2025-3-22 14:13

作者: 生氣的邊緣    時間: 2025-3-22 17:35
Graph Convolutional Networks,ural networks (CNNs) have achieved great success in the area of deep learning, it is intuitive to define the convolution operation on graphs. Advances in this direction are often categorized as spectral approaches and spatial approaches. As there may have vast variants in each direction, we only list several classic models in this chapter.
作者: 可能性    時間: 2025-3-22 22:39

作者: transdermal    時間: 2025-3-23 01:30

作者: 我說不重要    時間: 2025-3-23 08:31

作者: municipality    時間: 2025-3-23 12:30

作者: Indelible    時間: 2025-3-23 14:12

作者: collateral    時間: 2025-3-23 18:20

作者: NADIR    時間: 2025-3-24 02:15
Graph Recurrent Networks,tep to diminish the restrictions from the vanilla GNN model and improve the effectiveness of the long-term information propagation across the graph. In this chapter, we will talk about several variants and we call them Graph Recurrent Networks (GRNs).
作者: 懶洋洋    時間: 2025-3-24 04:39

作者: 曲解    時間: 2025-3-24 06:31

作者: 小丑    時間: 2025-3-24 11:14
Variants for Different Graph Types, graph format. However, there are many variants of graphs in the world and modeling different graph types requires different GNN structures. In this chapter, we investigate graph neural networks designed for specific graph types.
作者: 開花期女    時間: 2025-3-24 18:08

作者: 得罪    時間: 2025-3-24 20:24

作者: 燈絲    時間: 2025-3-25 01:09

作者: goodwill    時間: 2025-3-25 05:19

作者: 隨意    時間: 2025-3-25 09:13
Zhiyuan Liu,Jie Zhoum First publication on a woman philosopher, physicist and ma.Emilie du Chatelet was one of the most influential woman?philosophers of the Enlightenment. Her writings on natural philosophy, physics, and mechanics had a decisive impact on?important scientific debates of the 18th century. Particularly,
作者: 招致    時間: 2025-3-25 15:05

作者: 背心    時間: 2025-3-25 16:26
Zhiyuan Liu,Jie Zhoum First publication on a woman philosopher, physicist and ma.Emilie du Chatelet was one of the most influential woman?philosophers of the Enlightenment. Her writings on natural philosophy, physics, and mechanics had a decisive impact on?important scientific debates of the 18th century. Particularly,
作者: Hangar    時間: 2025-3-25 21:02

作者: LATER    時間: 2025-3-26 03:59

作者: 散開    時間: 2025-3-26 07:01

作者: GORGE    時間: 2025-3-26 10:25
Zhiyuan Liu,Jie Zhoum First publication on a woman philosopher, physicist and ma.Emilie du Chatelet was one of the most influential woman?philosophers of the Enlightenment. Her writings on natural philosophy, physics, and mechanics had a decisive impact on?important scientific debates of the 18th century. Particularly,
作者: MAUVE    時間: 2025-3-26 13:53
Zhiyuan Liu,Jie Zhoum First publication on a woman philosopher, physicist and ma.Emilie du Chatelet was one of the most influential woman?philosophers of the Enlightenment. Her writings on natural philosophy, physics, and mechanics had a decisive impact on?important scientific debates of the 18th century. Particularly,
作者: SENT    時間: 2025-3-26 20:52
Zhiyuan Liu,Jie Zhoum First publication on a woman philosopher, physicist and ma.Emilie du Chatelet was one of the most influential woman?philosophers of the Enlightenment. Her writings on natural philosophy, physics, and mechanics had a decisive impact on?important scientific debates of the 18th century. Particularly,
作者: ALLEY    時間: 2025-3-26 21:35
Zhiyuan Liu,Jie Zhoum First publication on a woman philosopher, physicist and ma.Emilie du Chatelet was one of the most influential woman?philosophers of the Enlightenment. Her writings on natural philosophy, physics, and mechanics had a decisive impact on?important scientific debates of the 18th century. Particularly,
作者: 準則    時間: 2025-3-27 04:05
Book 2020ity, GNN has recently become a widely applied graph analysis tool..This book provides a comprehensive introduction to the basic concepts, models, and applications of graph neural networks. It starts with the introduction of the vanilla GNN model. Then several variants of the vanilla model are introd
作者: 尊嚴    時間: 2025-3-27 08:59
1939-4608 dels, and applications of graph neural networks. It starts with the introduction of the vanilla GNN model. Then several variants of the vanilla model are introd978-3-031-00459-9978-3-031-01587-8Series ISSN 1939-4608 Series E-ISSN 1939-4616
作者: 音的強弱    時間: 2025-3-27 10:43
Zhiyuan Liu,Jie Zhou.Principia...The chapters presented here collectively demonstrate that her work was an essential contribution to? the mediation between empiricist and rationalist positions in the history of science..978-94-007-3693-1978-94-007-2093-0Series ISSN 0066-6610 Series E-ISSN 2215-0307
作者: Confess    時間: 2025-3-27 15:21

作者: photopsia    時間: 2025-3-27 20:38

作者: 故意    時間: 2025-3-27 23:52
Zhiyuan Liu,Jie Zhou.Principia...The chapters presented here collectively demonstrate that her work was an essential contribution to? the mediation between empiricist and rationalist positions in the history of science..978-94-007-3693-1978-94-007-2093-0Series ISSN 0066-6610 Series E-ISSN 2215-0307
作者: Yag-Capsulotomy    時間: 2025-3-28 03:09
Zhiyuan Liu,Jie Zhou.Principia...The chapters presented here collectively demonstrate that her work was an essential contribution to? the mediation between empiricist and rationalist positions in the history of science..978-94-007-3693-1978-94-007-2093-0Series ISSN 0066-6610 Series E-ISSN 2215-0307
作者: Hypopnea    時間: 2025-3-28 10:11
Zhiyuan Liu,Jie Zhou.Principia...The chapters presented here collectively demonstrate that her work was an essential contribution to? the mediation between empiricist and rationalist positions in the history of science..978-94-007-3693-1978-94-007-2093-0Series ISSN 0066-6610 Series E-ISSN 2215-0307
作者: 確定的事    時間: 2025-3-28 11:51
Zhiyuan Liu,Jie Zhou.Principia...The chapters presented here collectively demonstrate that her work was an essential contribution to? the mediation between empiricist and rationalist positions in the history of science..978-94-007-3693-1978-94-007-2093-0Series ISSN 0066-6610 Series E-ISSN 2215-0307
作者: 伸展    時間: 2025-3-28 15:48
Zhiyuan Liu,Jie Zhou.Principia...The chapters presented here collectively demonstrate that her work was an essential contribution to? the mediation between empiricist and rationalist positions in the history of science..978-94-007-3693-1978-94-007-2093-0Series ISSN 0066-6610 Series E-ISSN 2215-0307
作者: 灌輸    時間: 2025-3-28 18:46
Zhiyuan Liu,Jie Zhou.Principia...The chapters presented here collectively demonstrate that her work was an essential contribution to? the mediation between empiricist and rationalist positions in the history of science..978-94-007-3693-1978-94-007-2093-0Series ISSN 0066-6610 Series E-ISSN 2215-0307
作者: microscopic    時間: 2025-3-29 01:59

作者: orient    時間: 2025-3-29 06:42

作者: cinder    時間: 2025-3-29 07:29

作者: 潛伏期    時間: 2025-3-29 14:48

作者: 奇思怪想    時間: 2025-3-29 19:22
General Frameworks,6, Watters et al., 2017], Neural Physics Engine [Chang et al., 2017], CommNet [Sukhbaatar et al., 2016], structure2vec [Dai et al., 2016, Khalil et al., 2017], GGNN [Li et al., 2016], Relation Network [Raposo et al., 2017, Santoro et al., 2017], Deep Sets [Zaheer et al., 2017], and Point Net [Qi et al., 2017a].
作者: Creatinine-Test    時間: 2025-3-29 23:27

作者: 泥瓦匠    時間: 2025-3-30 02:32
Basics of Neural Networks,s rather precisely. In the end, the knowledge that a neural network learned is stored in the connections in a digital manner. Most of the researches on neural network try to change the way it learns (with different algorithms or different structures), aiming to improve the generalization ability of the model.
作者: 使習慣于    時間: 2025-3-30 06:25
Applications - Structural Scenarios,discussing how to model real-world physical systems with object-relationship graphs, how to predict chemical properties of molecules and biological interaction properties of proteins and the methods of reasoning about the out-of-knowledge-base (OOKB) entities in knowledge graphs.
作者: 鍍金    時間: 2025-3-30 10:35

作者: DAFT    時間: 2025-3-30 15:22
Graph Residual Networks,ce and deeper models could even perform worse [Kipf and Welling, 2017]. This is mainly because more layers could also propagate the noisy information from an exponentially increasing number of expanded neighborhood members.
作者: Perigee    時間: 2025-3-30 19:02





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