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gptkbp:instanceOf
|
gptkb:convolutional_neural_network
|
|
gptkbp:activatedBy
|
gptkb:ReLU
|
|
gptkbp:benchmarkDataset
|
gptkb:Cora
gptkb:Citeseer
Pubmed
|
|
gptkbp:citation
|
high
|
|
gptkbp:coreOperation
|
convolution on graphs
|
|
gptkbp:field
|
gptkb:machine_learning
graph representation learning
|
|
gptkbp:fullName
|
gptkb:Graph_Convolutional_Network
|
|
https://www.w3.org/2000/01/rdf-schema#label
|
GCN
|
|
gptkbp:influenced
|
many graph neural network models
|
|
gptkbp:influencedBy
|
gptkb:convolutional_neural_network
|
|
gptkbp:input
|
graph
adjacency matrix
node features
|
|
gptkbp:introduced
|
gptkb:Thomas_Kipf
gptkb:Max_Welling
|
|
gptkbp:introducedIn
|
2016
|
|
gptkbp:layer
|
graph convolution layer
|
|
gptkbp:limitation
|
cannot handle edge features directly
over-smoothing
scalability to large graphs
|
|
gptkbp:lossFunction
|
cross-entropy
|
|
gptkbp:mainActivity
|
graph classification
link prediction
node classification
|
|
gptkbp:openSource
|
gptkb:TensorFlow
gptkb:PyTorch_Geometric
DGL
|
|
gptkbp:parameter
|
learning rate
dropout rate
hidden dimension
number of layers
|
|
gptkbp:publishedIn
|
gptkb:arXiv:1609.02907
|
|
gptkbp:relatedTo
|
gptkb:GraphSAGE
gptkb:convolutional_neural_network
gptkb:GAT
|
|
gptkbp:title
|
gptkb:Semi-Supervised_Classification_with_Graph_Convolutional_Networks
|
|
gptkbp:trainer
|
backpropagation
|
|
gptkbp:usedIn
|
bioinformatics
recommendation systems
social network analysis
chemoinformatics
|
|
gptkbp:variant
|
gptkb:ChebNet
gptkb:FastGCN
gptkb:GCNII
gptkb:ResGCN
gptkb:Simplified_GCN
|
|
gptkbp:bfsParent
|
gptkb:convolutional_neural_network
gptkb:Advanced_Micro_Devices
|
|
gptkbp:bfsLayer
|
5
|