pgl
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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
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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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