原创 論文閱讀 TEMPORAL GRAPH NETWORKS FOR DEEP LEARNING ON DYNAMIC GRAPHS

14 TEMPORAL GRAPH NETWORKS FOR DEEP LEARNING ON DYNAMIC GRAPHS link:https://scholar.google.com.hk/scholar_url?url=https:

原创 論文閱讀 A Data-Driven Graph Generative Model for Temporal Interaction Networks

13 A Data-Driven Graph Generative Model for Temporal Interaction Networks link:https://scholar.google.com.sg/scholar_ur

原创 論文閱讀 Inductive Representation Learning on Temporal Graphs

12 Inductive Representation Learning on Temporal Graphs link:https://arxiv.org/abs/2002.07962 本文提出了時間圖注意(TGAT)層,以有效地聚合時間

原创 論文閱讀 GloDyNE Global Topology Preserving Dynamic Network Embedding

11 GloDyNE Global Topology Preserving Dynamic Network Embedding link:http://arxiv.org/abs/2008.01935 Abstract 目前大多數現有的DN

原创 論文閱讀 Exploring Temporal Information for Dynamic Network Embedding

10 Exploring Temporal Information for Dynamic Network Embedding 5 link:https://scholar.google.com.sg/scholar_url?url=htt

原创 論文閱讀 dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning

6 dyngraph2vec: Capturing Network Dynamics using Dynamic Graph Representation Learning207 link:https://scholar.google.co

原创 論文閱讀 Dynamic Network Embedding by Modeling Triadic Closure Process

3 Dynamic Network Embedding by Modeling Triadic Closure Process link:https://scholar.google.com.sg/scholar_url?url=http

原创 論文閱讀 Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks

6 Predicting Dynamic Embedding Trajectory in Temporal Interaction Networks link:https://arxiv.org/abs/1908.01207 Abstrac

原创 論文閱讀 DyREP:Learning Representations Over Dynamic Graphs

5 DyREP:Learning Representations Over Dynamic Graphs link:https://scholar.google.com/scholar_url?url=https://par.nsf.gov

原创 論文閱讀 Dynamic Graph Representation Learning Via Self-Attention Networks

4 Dynamic Graph Representation Learning Via Self-Attention Networks link:https://arxiv.org/abs/1812.09430 Abstract 提出了在動

原创 論文閱讀 Streaming Graph Neural Networks

3 Streaming Graph Neural Networks link:https://dl.acm.org/doi/10.1145/3397271.3401092 Abstract 本文提出了一種新的動態圖神經網絡模型DGNN,它可

原创 論文閱讀 DynGEM: Deep Embedding Method for Dynamic Graphs

2 DynGEM: Deep Embedding Method for Dynamic Graphs link:https://arxiv.org/abs/1805.11273v1 Abstract 首先這個嵌入是基於deep autoen

原创 論文閱讀 Continuous-Time Dynamic Network Embeddings

1 Continuous-Time Dynamic Network Embeddings Abstract ​ 描述一種將時間信息納入網絡嵌入的通用框架,該框架提出了從CTDG中學習時間相關嵌入 Conclusion ​ 描述了一個將時間信

原创 關於double精度的問題

題目 在平面直角座標系中,兩點可以確定一條直線。如果有多點在一條直線上,那麼這些點中任意兩點確定的直線是同一條。 給定平面上 2 × 3 個整點 { ( x , y ) ∣ 0 ≤ x < 2 , 0 ≤ y < 3 , x ∈ Z , y

原创 idea下servlet+jdbc的踩坑經歷

一 問題綜述 首先自己寫了一個網站頁面 <form action="add" method="post"> 名稱:<input type="text" name="fname"/><br/> 價格:<inp