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Recently, Graph Neural Networks (GNNs) have greatly advanced the task of graph classification.
Gao, H.; and Ji, S. 2019 · 1905
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ASAP: Adaptive Structure Aware Pooling for Learning Hierarchical Graph Representations
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A fair comparison of graph neural networks for graph classification
Errica, F.; Podda, M.; Bacciu, D.; and Micheli, A. 2019 · 1912
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Multi-channel graph neural networks
Zhou, K.; Song, Q.; Huang, X.; Zha, D.; Zou, N.; and Hu, X. 2019 · 1912
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Approximation capabilities of multilayer feedforward networks
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Distinguishing enzyme structures from non-enzymes without alignments
Dobson, P. D.; and Doig, A. J. 2003 · 2003
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Protein function prediction via graph kernels
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Visualizing data using t-SNE
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Weisfeiler-lehman graph kernels
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Convolutional networks on graphs for learning molecular fingerprints
Duvenaud, D. K.; Maclaurin, D.; Iparraguirre, J.; Bombarell, R.; Hirzel, T.; Aspuru-Guzik, A.; and Adams, R. P. 2015 · 2015
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Deep graph kernels
Yanardag, P.; and Vishwanathan, S. 2015 · 2015
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Convolutional neural networks on graphs with fast localized spectral filtering
Defferrard, M.; Bresson, X.; and Vandergheynst, P. 2016 · 2016
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Deep residual learning for image recognition
He, K.; Zhang, X.; Ren, S.; and Sun, J. 2016 · 2016
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Semi-supervised classification with graph convolutional networks
Kipf, T. N.; and Welling, M. 2016 · 2016
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Neural message passing for quantum chemistry
Gilmer, J.; Schoenholz, S. S.; Riley, P. F.; Vinyals, O.; and Dahl, G. E. 2017 · 2017
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Inductive representation learning on large graphs
Hamilton, W.; Ying, Z.; and Leskovec, J. 2017 · 2017
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Deep convolutional neural networks for image classification: A comprehensive review
ANRL: Attributed Network Representation Learning via Deep Neural Networks
Zhang, Z.; Yang, H.; Bu, J.; Zhou, S.; Yu, P.; Zhang, J.; Ester, M.; and Wang, C. 2018 · 2018
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Text classification algorithms: A survey
Kowsari, K.; Jafari Meimandi, K.; Heidarysafa, M.; Mendu, S.; Barnes, L.; and Brown, D. 2019 · 2019
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Graph convolutional networks with eigenpooling
Ma, Y.; Wang, S.; Aggarwal, C. C.; and Tang, J. 2019 · 2019
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Speech recognition using deep neural networks: A systematic review
Nassif, A. B.; Shahin, I.; Attili, I.; Azzeh, M.; and Shaalan, K. 2019 · 2019
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Graph Convolutional Neural Networks For Alzheimer’s Disease Classification
Song, T.-A.; Chowdhury, S. R.; Yang, F.; Jacobs, H.; El Fakhri, G.; Li, Q.; Johnson, K.; and Dutta, J. 2019 · 2019
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Graph Pooling with Representativeness
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Rawat, W.; and Wang, Z. 2017 · 2017
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Veličković, P.; Cucurull, G.; Casanova, A.; Romero, A.; Lio, P.; and Bengio, Y. 2017 · 2017
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Bert: Pre-training of deep bidirectional transformers for language understanding
Devlin, J.; Chang, M.-W.; Lee, K.; and Toutanova, K. 2018 · 2018
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SplineCNN: Fast geometric deep learning with continuous B-spline kernels
Fey, M.; Eric Lenssen, J.; Weichert, F.; and Müller, H. 2018 · 2018
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Film: Visual reasoning with a general conditioning layer
Perez, E.; Strub, F.; De Vries, H.; Dumoulin, V.; and Courville, A. 2018 · 2018
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Hierarchical graph representation learning with differentiable pooling
Ying, Z.; You, J.; Morris, C.; Ren, X.; Hamilton, W.; and Leskovec, J. 2018 · 2018
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Li, J.; Ma, Y.; Wang, Y.; Aggarwal, C.; Wang, C.-D.; and Tang, J. 2020 · 2020
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Self-Supervised Graph Transformer on Large-Scale Molecular Data
Rong, Y.; Bian, Y.; Xu, T.; Xie, W.; Wei, Y.; Huang, W.; and Huang, J. 2020 · 2020
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Composition-based Multi-Relational Graph Convolutional Networks
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StructPool: Structured Graph Pooling via Conditional Random Fields
Yuan, H.; and Ji, S. 2020 · 2020
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Topology-aware graph pooling networks
Gao, H.; Liu, Y.; and Ji, S. 2021 · 2021
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