1-6 深度图卷积神经网络模型探索.pdf

1、Building Very Deep Graph Neural Networks for Representation Learning on GraphsGuohao Li CS PhD Student KAUSTguohao.likaust.edu.saBuilding Very Deep Graph Neural Networks for Representation Learning on GraphsBuilding Very Deep Graph Neural Networks for Representation Learning on Graphs4Discussion:To

2、deep or not to deep2Making GCNs Go as Deep as CNNs:Message Aggregation Functions;Memory Efficiency3Designing GCNs automatically:Sequential Greedy Architecture Search;Latency Constrained;1Skip Connections and Dilated Convolutions on GraphsMaking GCNs Go as Deep as CNNs:Building Very Deep Graph Neural

3、 Networks for Representation Learning on GraphsGeneral Graphs：Social NetworksCitation NetworksLots of real-world applications need to deal with Non-Grid dataDeepGCNs.orgGraph dataBuilding Very Deep Graph Neural Networks for Representation Learning on GraphsGeneral Graphs：Social NetworksCitation Netw

4、orksMoleculesLots of real-world applications need to deal with Non-Grid dataDeepGCNs.orgGraph dataBuilding Very Deep Graph Neural Networks for Representation Learning on GraphsGeneral Graphs：Social NetworksCitation NetworksMoleculesPoint Clouds3D Meshes.Lots of real-world applications need to deal w

5、ith Non-Grid dataDeepGCNs.orgGraph dataBuilding Very Deep Graph Neural Networks for Representation Learning on GraphsKipf,T.N.and Welling,M.,2016.Semi-Supervised Classification with Graph Convolutional Networks.Velikovi,P.,Cucurull,G.,Casanova,A.,Romero,A.,Li,P.and Bengio,Y.,2018.Graph Attention Net

6、works.Wang,Y.,Sun,Y.,Liu,Z.,Sarma,S.E.,Bronstein,M.M.and Solomon,J.M.,2018.Dynamic Graph CNN for Learning on Point Clouds.Hamilton,W.L.,Ying,R.and Leskovec,J.,2017.Inductive Representation Learning on Large Graphs.Most of SOTA GNNs are not deeper than 3 or 4 layers.Building Very Deep Graph Neural Ne