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2101.01849
Cited By

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks

Node2Seq: Towards Trainable Convolutions in Graph Neural Networks

6 January 2021

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Papers citing "Node2Seq: Towards Trainable Convolutions in Graph Neural Networks"

5 / 5 papers shown

Refining Latent Homophilic Structures over Heterophilic Graphs for
Robust Graph Convolution Networks

Refining Latent Homophilic Structures over Heterophilic Graphs for Robust Graph Convolution Networks

337

13

0

27 Dec 2023

Boosting Graph Structure Learning with Dummy Nodes

Boosting Graph Structure Learning with Dummy NodesInternational Conference on Machine Learning (ICML), 2022

Xin Liu

Xin Jiang

194

27

0

17 Jun 2022

Graph Pointer Neural Networks

Graph Pointer Neural Networks

Yujing Wang

Jing Bai

274

52

0

03 Oct 2021

Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond
Message Passing

Walking Out of the Weisfeiler Leman Hierarchy: Graph Learning Beyond Message Passing

509

47

0

17 Feb 2021

On Explainability of Graph Neural Networks via Subgraph Explorations

On Explainability of Graph Neural Networks via Subgraph ExplorationsInternational Conference on Machine Learning (ICML), 2021

Haiyang Yu

438

496

0

09 Feb 2021

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