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14 TEMPORAL GRAPH NETWORKS FOR DEEP LEARNING ON DYNAMIC GRAPHS link:https://scholar.google.com.hk/scholar_url?url=https://arxiv.org/pdf/2006.10637.pdf 阅读全文
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13 A Data-Driven Graph Generative Model for Temporal Interaction Networks link:https://scholar.google.com.sg/scholar_url?url=https://par.nsf.gov/servl 阅读全文
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12 Inductive Representation Learning on Temporal Graphs link:https://arxiv.org/abs/2002.07962 本文提出了时间图注意(TGAT)层，以有效地聚合时间-拓扑邻域特征，并学习时间-特征之间的相互作用。对于TGAT 阅读全文
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11 GloDyNE Global Topology Preserving Dynamic Network Embedding link:http://arxiv.org/abs/2008.01935 Abstract 目前大多数现有的DNE方法的思想是捕捉最受影响的节点(而不是所有节点)或周围的拓 阅读全文
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10 Exploring Temporal Information for Dynamic Network Embedding 5 link:https://scholar.google.com.sg/scholar_url?url=https://ieeexplore.ieee.org/abstr 阅读全文
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9 Real-Time Streaming Graph Embedding Through Local Actions 11 link:https://scholar.google.com.sg/scholar_url?url=https://par.nsf.gov/servlets/purl/10 阅读全文
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#6 dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning207 link：https://scholar.google.com.hk/scholar_url?url=https:// 阅读全文
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3 Dynamic Network Embedding by Modeling Triadic Closure Process link:https://scholar.google.com.sg/scholar_url?url=https://ojs.aaai.org/index.php/AAAI 阅读全文
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7 Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks link:https://arxiv.org/abs/1908.01207 Abstract 本文提出了一种在嵌入空间中显示建模用户/项目的未来轨迹的 阅读全文
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6 DyREP:Learning Representations Over Dynamic Graphs link:https://scholar.google.com/scholar_url?url=https://par.nsf.gov/servlets/purl/10099025&hl=zh- 阅读全文