Semi-Supervised Classification with Graph Convolutional Networks.

Articles citing Semi-Supervised Classification with Graph Convolutional Networks.

Title / Author	Year
Inductive representation learning on large graphs W Hamilton, Z Ying, J Leskovec Advances in neural information processing systems, 1024-1034	2017
Graph attention networks P Veličković, G Cucurull, A Casanova, A Romero, P Lio, Y Bengio arXiv preprint arXiv:1710.10903	2017
Neural message passing for quantum chemistry J Gilmer, SS Schoenholz, PF Riley, O Vinyals, GE Dahl arXiv preprint arXiv:1704.01212	2017
Geometric deep learning: going beyond euclidean data MM Bronstein, J Bruna, Y LeCun, A Szlam, P Vandergheynst IEEE Signal Processing Magazine 34 (4), 18-42	2017
A simple neural network module for relational reasoning A Santoro, D Raposo, DG Barrett, M Malinowski, R Pascanu, P Battaglia, ... Advances in neural information processing systems, 4967-4976	2017
Representation learning on graphs: Methods and applications WL Hamilton, R Ying, J Leskovec arXiv preprint arXiv:1709.05584	2017
Geometric deep learning on graphs and manifolds using mixture model cnns F Monti, D Boscaini, J Masci, E Rodola, J Svoboda, MM Bronstein Proceedings of the IEEE Conference on Computer Vision and Pattern …	2017
Modeling relational data with graph convolutional networks M Schlichtkrull, TN Kipf, P Bloem, R Van Den Berg, I Titov, M Welling European Semantic Web Conference, 593-607	2018
Dynamic graph cnn for learning on point clouds Y Wang, Y Sun, Z Liu, SE Sarma, MM Bronstein, JM Solomon Acm Transactions On Graphics (tog) 38 (5), 1-12	2019
How powerful are graph neural networks? K Xu, W Hu, J Leskovec, S Jegelka arXiv preprint arXiv:1810.00826	2018
Deep learning based recommender system: A survey and new perspectives S Zhang, L Yao, A Sun, Y Tay ACM Computing Surveys (CSUR) 52 (1), 1-38	2019
A comprehensive survey of graph embedding: Problems, techniques, and applications H Cai, VW Zheng, KCC Chang IEEE Transactions on Knowledge and Data Engineering 30 (9), 1616-1637	2018
A review on deep learning techniques applied to semantic segmentation A Garcia-Garcia, S Orts-Escolano, S Oprea, V Villena-Martinez, ... arXiv preprint arXiv:1704.06857	2017
Variational graph auto-encoders TN Kipf, M Welling arXiv preprint arXiv:1611.07308	2016
Spatial temporal graph convolutional networks for skeleton-based action recognition S Yan, Y Xiong, D Lin Thirty-second AAAI conference on artificial intelligence	2018
A comprehensive survey on graph neural networks Z Wu, S Pan, F Chen, G Long, C Zhang, SY Philip IEEE Transactions on Neural Networks and Learning Systems	2020
Graph convolutional neural networks for web-scale recommender systems R Ying, R He, K Chen, P Eksombatchai, WL Hamilton, J Leskovec Proceedings of the 24th ACM SIGKDD International Conference on Knowledge …	2018
Graph neural networks: A review of methods and applications J Zhou, G Cui, Z Zhang, C Yang, Z Liu, L Wang, C Li, M Sun arXiv preprint arXiv:1812.08434	2018
The rise of deep learning in drug discovery H Chen, O Engkvist, Y Wang, M Olivecrona, T Blaschke Drug discovery today 23 (6), 1241-1250	2018
Convolutional 2d knowledge graph embeddings T Dettmers, P Minervini, P Stenetorp, S Riedel Thirty-Second AAAI Conference on Artificial Intelligence	2018

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