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awesome-graph's Introduction

Awesome-Graph

Survey

  • A Comprehensive Survey on Graph Neural Networks

Basic papers

  • Graph Attention Networks(GAT)
  • Inductive Representation Learning on Large Graphs(GraphSage)
  • Semi-Supervised Classification with Graph Convolutional Networks(GCN)
  • Simplifying Graph Convolutional Networks
  • Self-Attention Graph Pooling
  • GMNN: Graph Markov Neural Networks
  • (AAAI2018) Deeper Insights into Graph Convolutional Networks
  • (KDD2019) Heterogeneous Graph Neural Network
  • (WWW2019) Heterogeneous Graph Attention Network

Recommender System

Prediction

  • (WWW2020)Traffic Flow Prediction via Spatial Temporal Graph Neural Network
  • T-GCN: A Temporal Graph Convolutional Network for Traffic Prediction

NLP

  • Graph Convolutional Networks for Text Classification
  • Hierarchical Graph Convolutional Networks for Semi-supervised Node Classification
  • (EMNLP2017)Graph Convolutional Encoders for Syntax-aware Neural Machine Translation
  • (CIKM2018)Multiresolution Graph Attention Networks for Relevance Matching
  • (EMNLP2019) Heterogeneous Graph Attention Networks for Semi-supervised Short Text Classification
  • (CIKM2019) Spam Review Detection with Graph Convolutional Networks
  • (AAAI2019)Personalized Question Routing via Heterogeneous Network Embedding
  • (AAAI2020)Tensor Graph Convolutional Networks for Text Classification
  • (ACL2020)Heterogeneous Graph Neural Networks for Extractive Document Summarization
  • (WWW2018)Dual Graph Convolutional Networks for Graph-Based Semi-Supervised Classification
  • (ACL2020)GCAN: Graph-aware Co-Attention Networks for Explainable Fake News Detection on Social Media
  • (ACL2020)Relational Graph Attention Network for Aspect-based Sentiment Analysis

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