Policy-GNN: Aggregation Optimization for Graph Neural Networks

Author:

Lai Kwei-Herng1,Zha Daochen1,Zhou Kaixiong1,Hu Xia1

Affiliation:

1. Texas A&M University, College Station, TX, USA

Funder

National Science Foundation

Publisher

ACM

Reference46 articles.

1. Peter W Battaglia Jessica B Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vinicius Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner etal 2018. Relational inductive biases deep learning and graph networks. arXiv preprint arXiv:1806.01261 (2018). Peter W Battaglia Jessica B Hamrick Victor Bapst Alvaro Sanchez-Gonzalez Vinicius Zambaldi Mateusz Malinowski Andrea Tacchetti David Raposo Adam Santoro Ryan Faulkner et al. 2018. Relational inductive biases deep learning and graph networks. arXiv preprint arXiv:1806.01261 (2018).

2. Jie Chen Tengfei Ma and Cao Xiao. 2018. FastGCN: Fast learning with graph convolutional networks via importance sampling. In ICLR. Jie Chen Tengfei Ma and Cao Xiao. 2018. FastGCN: Fast learning with graph convolutional networks via importance sampling. In ICLR.

3. Jie Chen Tengfei Ma and Cao Xiao. 2018. FastGCN: Fast learning with graph convolutional networks via importance sampling. In ICLRs. Jie Chen Tengfei Ma and Cao Xiao. 2018. FastGCN: Fast learning with graph convolutional networks via importance sampling. In ICLRs.

4. Michaël Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In NeurIPS. Michaël Defferrard Xavier Bresson and Pierre Vandergheynst. 2016. Convolutional neural networks on graphs with fast localized spectral filtering. In NeurIPS.

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