Heterogeneous Deep Graph Infomax

Last update: Oct 31, 2022

Overview

Heterogeneous-Deep-Graph-Infomax

Parameter Setting:

HDGI-A:

Node-level dimension: 16
Attention head: 4
Semantic-level attention vector: 8
learning rate: 0.02

HDGI-C:

Node-level dimension: 64
Semantic-level attention vector: 8
learning rate: 0.02

GAT:

Node-level dimension: 16
Attention head: 4
learning rate: 0.005
Drop out ratio: 0.6

GCN:

Hidden-unit dimension: 64
learning rate: 0.01
Drop out ratio: 0.5

RGCN:

Hidden-unit dimension: 16
learning rate: 0.01
Drop out ratio: 0

Metapath2Vec:

Embedding dimension: 100
learning rate: 0.01
negative-samples: 5
Window: 1

HAN:

Node-level dimension: 16
Attention head: 4
Semantic-level dimension: 8
learning rate: 0.005
Node-level Drop out ratio: 0.6
Semantic-level Drop out ratio: 0.6

Deepwalk:

Number of walks per node: 10
Dimensions of word embeddings: 128
Length of random walk: 30
Window size for skipgram: 5

DGI:

Hidden-unit dimension: 64
learning rate: 0.001
Drop out ratio: 0

Owner

GitHub Repository

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