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Modern machine learning techniques are successfully being adapted to data modeled as graphs.
Metis—a software package for partitioning unstructured graphs, partitioning meshes and computing fill-reducing ordering of sparse matrices
George Karypis and Vipin Kumar · 1997
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Distributed representations of words and phrases and their compositionality
Tomas Mikolov, Ilya Sutskever, Kai Chen, Greg Corrado, and Jeffrey Dean · 2013
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Spectral networks and locally connected networks on graphs
Joan Bruna, Wojciech Zaremba, Arthur Szlam, and Yann LeCun · 2014
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Adam: A method for stochastic optimization
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J. Ahn, S. Hong, S. Yoo, O. Mutlu, and K. Choi · 2015
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Deep convolutional networks on graph-structured data
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Qsgd: Communication-efficient sgd via gradient quantization and encoding
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Protein interface prediction using graph convolutional networks
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Adaptive sampling towards fast graph representation learning
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Cluster-gcn: An efficient algorithm for training deep and large graph convolutional networks
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Fast graph representation learning with PyTorch Geometric
Matthias Fey and Jan E. Lenssen · 2019
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Terngrad: Ternary gradients to reduce communication in distributed deep learning
Wei Wen, Cong Xu, Feng Yan, Chunpeng Wu, Yandan Wang, Yiran Chen, and Hai Li · 2017
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FastGCN: Fast learning with graph convolutional networks via importance sampling
Jie Chen, Tengfei Ma, and Cao Xiao · 2018
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Representation learning on graphs: Methods and applications
William L. Hamilton, Rex Ying, and Jure Leskovec
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Inductive representation learning on large graphs
William L. Hamilton, Rex Ying, and Jure Leskovec
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Neugraph: Parallel deep neural network computation on large graphs
Lingxiao Ma, Zhi Yang, Youshan Miao, Jilong Xue, Ming Wu, Lidong Zhou, and Yafei Dai · 2019
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Aligraph: A comprehensive graph neural network platform
Hongxia Yang · 2019
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Improving the accuracy, scalability, and performance of graph neural networks with roc
Zhihao Jia, Sina Lin, Mingyu Gao, Matei Zaharia, and Alex Aiken · 2020
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A comprehensive survey on graph neural networks
Z. Wu, S. Pan, F. Chen, G. Long, C. Zhang, and P. S. Yu · 2020
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