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[1] P. Dobson,et al. Distinguishing enzyme structures from non-enzymes without alignments. , 2003, Journal of molecular biology.
[2] Ashwin Srinivasan,et al. Statistical Evaluation of the Predictive Toxicology Challenge 2000-2001 , 2003, Bioinform..
[3] Yizhou Sun,et al. Are Powerful Graph Neural Nets Necessary? A Dissection on Graph Classification , 2019, ArXiv.
[4] Zhi-Li Zhang,et al. Graph Capsule Convolutional Neural Networks , 2018, ArXiv.
[5] Chih-Jen Lin,et al. LIBLINEAR: A Library for Large Linear Classification , 2008, J. Mach. Learn. Res..
[6] Hans-Peter Kriegel,et al. Shortest-path kernels on graphs , 2005, Fifth IEEE International Conference on Data Mining (ICDM'05).
[7] Samuel S. Schoenholz,et al. Neural Message Passing for Quantum Chemistry , 2017, ICML.
[8] Hisashi Kashima,et al. Marginalized Kernels Between Labeled Graphs , 2003, ICML.
[9] Thomas Gärtner,et al. On Graph Kernels: Hardness Results and Efficient Alternatives , 2003, COLT.
[10] Kurt Mehlhorn,et al. Efficient graphlet kernels for large graph comparison , 2009, AISTATS.
[11] Richard S. Zemel,et al. Gated Graph Sequence Neural Networks , 2015, ICLR.
[12] Yoshua Bengio,et al. On Using Very Large Target Vocabulary for Neural Machine Translation , 2014, ACL.
[13] Nils M. Kriege,et al. A survey on graph kernels , 2019, Applied Network Science.
[14] Jure Leskovec,et al. Hierarchical Graph Representation Learning with Differentiable Pooling , 2018, NeurIPS.
[15] Yaron Lipman,et al. Provably Powerful Graph Networks , 2019, NeurIPS.
[16] Lihui Chen,et al. Capsule Graph Neural Network , 2018, ICLR.
[17] Quoc V. Le,et al. Distributed Representations of Sentences and Documents , 2014, ICML.
[18] Sergey Ivanov,et al. Anonymous Walk Embeddings , 2018, ICML.
[19] Hans-Peter Kriegel,et al. Protein function prediction via graph kernels , 2005, ISMB.
[20] Yaron Lipman,et al. Invariant and Equivariant Graph Networks , 2018, ICLR.
[21] Geoffrey E. Hinton,et al. Visualizing Data using t-SNE , 2008 .
[22] Jure Leskovec,et al. Inductive Representation Learning on Large Graphs , 2017, NIPS.
[23] Mathias Niepert,et al. Learning Convolutional Neural Networks for Graphs , 2016, ICML.
[24] Chengqi Zhang,et al. Network Representation Learning: A Survey , 2017, IEEE Transactions on Big Data.
[25] Lukasz Kaiser,et al. Attention is All you Need , 2017, NIPS.
[26] S. V. N. Vishwanathan,et al. Graph kernels , 2007 .
[27] Jeffrey Dean,et al. Distributed Representations of Words and Phrases and their Compositionality , 2013, NIPS.
[28] Hannu Toivonen,et al. Statistical evaluation of the predictive toxicology challenge , 2000 .
[29] Michalis Vazirgiannis,et al. Graph Kernels: A Survey , 2019, J. Artif. Intell. Res..
[30] Yang Liu,et al. graph2vec: Learning Distributed Representations of Graphs , 2017, ArXiv.
[31] A. Debnath,et al. Structure-activity relationship of mutagenic aromatic and heteroaromatic nitro compounds. Correlation with molecular orbital energies and hydrophobicity. , 1991, Journal of medicinal chemistry.
[32] Pinar Yanardag,et al. Deep Graph Kernels , 2015, KDD.
[33] Wenwu Zhu,et al. Deep Learning on Graphs: A Survey , 2018, IEEE Transactions on Knowledge and Data Engineering.
[34] Younjoo Seo,et al. Discriminative structural graph classification , 2019, ArXiv.
[35] Max Welling,et al. Semi-Supervised Classification with Graph Convolutional Networks , 2016, ICLR.
[36] Razvan Pascanu,et al. Relational inductive biases, deep learning, and graph networks , 2018, ArXiv.
[37] Ah Chung Tsoi,et al. The Graph Neural Network Model , 2009, IEEE Transactions on Neural Networks.
[38] Jian Sun,et al. Deep Residual Learning for Image Recognition , 2015, 2016 IEEE Conference on Computer Vision and Pattern Recognition (CVPR).
[39] Kurt Mehlhorn,et al. Weisfeiler-Lehman Graph Kernels , 2011, J. Mach. Learn. Res..
[40] Jure Leskovec,et al. How Powerful are Graph Neural Networks? , 2018, ICLR.
[41] Zhiyuan Liu,et al. Graph Neural Networks: A Review of Methods and Applications , 2018, AI Open.
[42] Jure Leskovec,et al. Representation Learning on Graphs: Methods and Applications , 2017, IEEE Data Eng. Bull..
[43] Philip S. Yu,et al. A Comprehensive Survey on Graph Neural Networks , 2019, IEEE Transactions on Neural Networks and Learning Systems.
[44] Yixin Chen,et al. An End-to-End Deep Learning Architecture for Graph Classification , 2018, AAAI.
[45] Geoffrey E. Hinton,et al. Dynamic Routing Between Capsules , 2017, NIPS.
[46] Jimmy Ba,et al. Adam: A Method for Stochastic Optimization , 2014, ICLR.
[47] Michael Rabadi,et al. Kernel Methods for Machine Learning , 2015 .