GNN架构/体系优质论文推荐

GNN Architecture ，研究GNN架构/体系，基本涵盖了GNN最经典、必读的文章，如基于谱图卷积的GCNs三部曲， 序列图神经网络GGNN，基于注意力机制的GAT等。

1.论文名称：Semi-Supervised Classification with Graph Convolutional Networks.
链接：https://www.aminer.cn/pub/58437722ac44360f1082efeb
2.论文名称：Deep Graph Infomax.
链接：https://www.aminer.cn/pub/5bdc31b417c44a1f58a0b4e9
3.论文名称：Graph Attention Networks.
链接：https://www.aminer.cn/pub/5a260c8117c44a4ba8a30f54
4.论文名称：MixHop: Higher-Order Graph Convolution Architectures via Sparsified Neighborhood Mixing.
链接：https://www.aminer.cn/pub/5ce3ae56ced107d4c65e7cdb
5.论文名称：Graph Random Neural Networks for Semi-Supervised Learning on Graphs
链接：https://www.aminer.cn/pub/5f7fdd328de39f0828397cc3
6.论文名称：DropEdge: Towards Deep Graph Convolutional Networks on Node Classification
链接：https://www.aminer.cn/pub/5e5e18de93d709897ce37796
7.论文名称：Convolutional Neural Networks on Graphs with Fast Localized Spectral Filtering.
链接：https://www.aminer.cn/pub/57a4e91aac44365e35c97c6e
8.论文名称：Predict then Propagate: Graph Neural Networks meet Personalized PageRank
链接：https://www.aminer.cn/pub/5ce2d032ced107d4c635260c
9.论文名称：Gated Graph Sequence Neural Networks
链接：https://www.aminer.cn/pub/5736960c6e3b12023e51ee06
10.论文名称：Inductive Representation Learning on Large Graphs.
链接：https://www.aminer.cn/pub/599c7988601a182cd2648a09
11.论文名称：Representation Learning on Graphs with Jumping Knowledge Networks.
链接：https://www.aminer.cn/pub/5b67b47917c44aac1c8637c6
12.论文名称：DeepGCNs: Can GCNs Go As Deep As CNNs?
链接：https://www.aminer.cn/pub/5e09aa66df1a9c0c416bebf6
13.论文名称：Training Graph Neural Networks with 1000 Layers
链接：https://www.aminer.cn/pub/60cae12b91e011b32937419e
14.论文名称：Simple and Deep Graph Convolutional Networks
链接：https://www.aminer.cn/pub/5ede0553e06a4c1b26a83f63
15.论文名称：Combining Label Propagation and Simple Models Out-performs Graph Neural Networks
链接：https://www.aminer.cn/pub/5f993ec291e011a3fbe2fb5c
16.论文名称：Graph Attention Multi-Layer Perceptron
链接：https://www.aminer.cn/pub/6125b00e5244ab9dcb38aed1
17.论文名称：How to Find Your Friendly Neighborhood: Graph Attention Design with Self-Supervision
链接：https://www.aminer.cn/pub/6008324a9e795ed227f530f9
18.论文名称：Towards Deeper Graph Neural Networks
链接：https://www.aminer.cn/pub/5f03f3b611dc83056223205d
19.论文名称：Graph Traversal with Tensor Functionals: A Meta-Algorithm for Scalable Learning
链接：https://www.aminer.cn/pub/600832539e795ed227f53101
20.论文名称：Diffusion Improves Graph Learning
链接：https://www.aminer.cn/pub/5db929b747c8f766461fa94f

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