【导读】作为世界数据挖掘领域的最高级别的学术会议,ACM SIGKDD(国际数据挖掘与知识发现大会,简称 KDD)每年都会吸引全球领域众多专业人士参与。今年的 KDD大会计划将于 2020 年 8 月 23 日 ~27 日在美国美国加利福尼亚州圣地亚哥举行。上周,KDD 2020官方发布接收论文,共有1279篇论文提交到Research Track,共216篇被接收,接收率16.8%。本文我们为大家整理收集了图神经网络专题系列的论文信息汇总。
KDD 2020 Accepted Paper:
链接:https://www.kdd.org/kdd2020/accepted-papers
GNN论文信息汇总
1. Graph Structure Learning for Robust Graph Neural Networks
2. Connecting the Dots: Multivariate Time Series Forecasting with Graph Neural Networks
3. Understanding Negative Sampling in Graph Representation Learning
4. M2GRL: A Multi-task Multi-view Graph Representation Learning Framework for Web-scale Recommender Systems
5. Controllable Multi-Interest Framework for Recommendation
6. Multi-level Graph Convolutional Networks for Cross-platform Anchor Link Prediction
7. GCC: Graph Contrastive Coding for Graph Neural Network Pre-Training
8. GHashing: Semantic Graph Hashing for Approximate Similarity Search in Graph Databases
9. Graph Structural-topic Neural Network
10. Minimal Variance Sampling with Provable Guarantees for Fast Training of Graph Neural Networks