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En^c@JvRn(BM!AxCm@=x(T9#OiQgYOn7Up~Z@`VL z&!tG7<-Uf(yNj8x8-0fRy+?ua%MM{g!3`uoL<3H>Jf7_d>>7|m+jLr8k>Xh23<<4NEjho@)#B9un8ID+ky(HGv? p|8cW4OY%?=&JWry^%}z_dH9yzKyqQ$9WwAoRr$J7p@K!={{sK0cvS!Z diff --git a/kglib/kgcn/README.md b/kglib/kgcn/README.md index cf10478f..6c9da782 100644 --- a/kglib/kgcn/README.md +++ b/kglib/kgcn/README.md @@ -68,13 +68,13 @@ for step in supersteps: Use as input the current edge features and the features of the nodes it connects. Update the edge's features as the output of some neural network layers. Do this for all edges. - +![Edge Update](.images/edge_update.png) ### Node Block Use as input the node's features and the most up-to-date features of the edges that connect to it. Update the node's features as the output of some neural network layers. Do this for all nodes. - +![Node Update](.images/node_update.png) ### How is this Convolutional?