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Graph Convolutional Networks (GCNs) have recently been shown to be quite successful in modeling graph-structured data.
Structure-activity relationship of mutagenic aromatic and heteroaromatic nitro compounds. correlation with molecular orbital energies and hydrophobicity
Asim Kumar Debnath, Rosa L. Lopez de Compadre, Gargi Debnath, Alan J. Shusterman, and Corwin Hansch · 1991
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Wordnet: A lexical database for english
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The predictive toxicology evaluation challenge
A. Srinivasan, R. D. King, S. H. Muggleton, and M. J. E. Sternberg · 1997
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Nino Shervashidze, Pascal Schweitzer, Erik Jan van Leeuwen, Kurt Mehlhorn, and Karsten M. Borgwardt · 2011
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Imagenet classification with deep convolutional neural networks
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Spectral networks and locally connected networks on graphs
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Reasoning with neural tensor networks for knowledge base completion
Richard Socher, Danqi Chen, Christopher D Manning, and Andrew Ng · 2013
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Question answering with subgraph embeddings
Antoine Bordes, Sumit Chopra, and Jason Weston · 2014
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Adam: A method for stochastic optimization
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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2014
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A review of relational machine learning for knowledge graphs
M. Nickel, K. Murphy, V. Tresp, and E. Gabrilovich · 2015
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Observed versus latent features for knowledge base and text inference
Kristina Toutanova and Danqi Chen · 2015
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Deep graph kernels
Pinar Yanardag and S.V.N. Vishwanathan · 2015
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Convolutional neural networks on graphs with fast localized spectral filtering
Michaël Defferrard, Xavier Bresson, and Pierre Vandergheynst · 2016
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2016
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Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, and Tomaso Poggio · 2016
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Learning convolutional neural networks for graphs
KBGAN: Adversarial learning for knowledge graph embeddings
Liwei Cai and William Yang Wang · 2018
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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Minervini Pasquale, Stenetorp Pontus, and Sebastian Riedel · 2018
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Dual-primal graph convolutional networks
Federico Monti, Oleksandr Shchur, Aleksandar Bojchevski, Or Litany, Stephan Günnemann, and Michael M. Bronstein · 2018
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Soumya Sanyal, Janakiraman Balachandran, Naganand Yadati, Abhishek Kumar, Padmini Rajagopalan, Suchismita Sanyal, and Partha Talukdar · 2018
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Graph Attention Networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Adriana Romero, Pietro Liò, and Yoshua Bengio · 2018
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A collection of benchmark datasets for systematic evaluations of machine learning on the semantic web
Petar Ristoski, Gerben Klaas Dirk de Vries, and Heiko Paulheim · 2016
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Complex embeddings for simple link prediction
Théo Trouillon, Johannes Welbl, Sebastian Riedel, Éric Gaussier, and Guillaume Bouchard · 2016
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Protein interface prediction using graph convolutional networks
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Neural message passing for quantum chemistry
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Inductive representation learning on large graphs
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An end-to-end deep learning architecture for graph classification
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Hypernetwork knowledge graph embeddings
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