[PDF] Simple and Deep Graph Convolutional Networks - ICML Proceedings
problem (Kipf Welling, 2017); deep GCN models are still in a multi layer GCN model, and we perform experiments to confirm In ICLR Workshop on Repre
[PDF] Learning Convolutional Neural Networks for Graphs
High bias GCN [ICLR 2017] Average Pooling Leverage complete adjacency structure Treat neighboring nodes as exchangeable ? Approximate lifted learning
[PDF] unsupervised pre-training of graph convolu- tional networks - Ziniu Hu
Published as a workshop paper at ICLR 2019 UNSUPERVISED GCN takes a graph with arbitrary features as input and applies convolution filters to generate
[PDF] HyperGCN: A New Method For Training Graph Convolutional
a graph convolutional network (GCN) has been effective for graph based SSL, In International Conference on Learning Representations (ICLR), 2017 1, 2, 3
[PDF] PairNorm: Tackling Oversmoothing in GNNS - Lingxiao Zhao
PairNorm Tackling Oversmoothing in GNNS Appearing in ICLR 2020 Graph Convolutional Neural Network (GCN) [Kipf 17] • Stacking of GraphConv layer
[PDF] graph attention networks - Mila Quebec
Published as a conference paper at ICLR 2018 GRAPH our model is upper bounded by the depth of the network (similarly as for GCN and similar models)
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