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12dd6876
编写于
10月 29, 2019
作者:
L
liweibin
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README.md
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@@ -85,7 +85,7 @@ In most cases of large-scale graph learning, we need distributed graph storage a
The following are 13 graph learning models that have been implemented in the framework.
|Model | feature |
|---|---|
--- |
|---|---|
| GCN | Graph Convolutional Neural Networks |
| GAT | Graph Attention Network |
| GraphSage |Large-scale graph convolution network based on neighborhood sampling|
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docs/source/md/introduction.md
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@@ -103,7 +103,7 @@ In most cases of large-scale graph learning, we need distributed graph storage a
The following are 13 graph learning models that have been implemented in the framework.
|Model | feature |
|---|---|
--- |
|---|---|
|
[
GCN
](
examples/gcn_examples.html
)
| Graph Convolutional Neural Networks |
|
[
GAT
](
examples/gat_examples.html
)
| Graph Attention Network |
|
[
GraphSage
](
examples/graphsage_examples.html
)
|Large-scale graph convolution network based on neighborhood sampling|
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