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Introduction

  • Paddle Graph Learning (PGL)

Quick Start

  • Quick Start Instructions
  • Quick Start with Heterogenous Graph

Examples

  • GCN: Graph Convolutional Networks
  • GAT: Graph Attention Networks
  • Using StaticGraphWrapper for Speed Optimization
  • node2vec: Scalable Feature Learning for Networks
  • GraphSAGE: Inductive Representation Learning on Large Graphs
  • DGI: Deep Graph Infomax
  • Distributed Deepwalk in PGL
  • Distribute GraphSAGE in PGL
  • GES: Graph Embedding with Side Information
  • LINE: Large-scale Information Network Embedding
  • SGC: Simplifying Graph Convolutional Networks
  • struc2vec: Learning Node Representations from Structural Identity
  • GATNE: General Attributed Multiplex HeTerogeneous Network Embedding
  • metapath2vec: Scalable Representation Learning for Heterogeneous Networks
  • Unsupervised GraphSAGE in PGL

API Reference

  • API Reference

The Team

  • The Team
pgl
  • Docs »
  • Overview: module code

All modules for which code is available

  • logging
  • pgl.data_loader
  • pgl.graph
  • pgl.graph_wrapper
  • pgl.heter_graph
  • pgl.heter_graph_wrapper
  • pgl.layers.conv
  • pgl.layers.graph_pool
  • pgl.layers.set2set
  • pgl.utils.mp_reader
  • pgl.utils.paddle_helper

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