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We propose Dynamically Pruned Message Passing Networks (DPMPN) for large-scale knowledge graph reasoning.
The nature of explanation
Kenneth H. Craik · 1952
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The graph neural network model
Franco Scarselli, Marco Gori, Ah Chung Tsoi, Markus Hagenbuchner, and Gabriele Monfardini · 2009
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Random walk inference and learning in a large scale knowledge base
Ni Lao, Tom Michael Mitchell, and William W. Cohen · 2011
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto García-Durán, Jason Weston, and Oksana Yakhnenko · 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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Yago3: A knowledge base from multilingual wikipedias
Farzaneh Mahdisoltani, Joanna Asia Biega, and Fabian M. Suchanek · 2014
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Knowledge graph embedding by translating on hyperplanes
Zhen Wang, Jianwen Zhang, Jianlin Feng, and Zheng Chen · 2014
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Neural machine translation by jointly learning to align and translate
Dzmitry Bahdanau, Kyunghyun Cho, and Yoshua Bengio · 2015
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Convolutional networks on graphs for learning molecular fingerprints
David K. Duvenaud, Dougal Maclaurin, Jorge Aguilera-Iparraguirre, Rafael Gómez-Bombarelli, Timothy Hirzel, Alán Aspuru-Guzik, and Ryan P. Adams · 2015
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Traversing knowledge graphs in vector space
Kelvin Guu, John Miller, and Percy S. Liang · 2015
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Deep convolutional networks on graph-structured data
Mikael Henaff, Joan Bruna, and Yann LeCun · 2015
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Knowledge graph embedding via dynamic mapping matrix
Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, and Jian Zhao · 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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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2015
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Interaction networks for learning about objects, relations and physics
Peter W. Battaglia, Razvan Pascanu, Matthew Lai, Danilo Jimenez Rezende, and Koray Kavukcuoglu · 2016
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Tensorlog: A differentiable deductive database
William W. Cohen · 2016
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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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Molecular graph convolutions: moving beyond fingerprints
Steven M. Kearnes, Kevin McCloskey, Marc Berndl, Vijay S. Pande, and Patrick Riley · 2016
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Gated graph sequence neural networks
Yujia Li, Daniel Tarlow, Marc Brockschmidt, and Richard S. Zemel · 2016
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Neural symbolic machines: Learning semantic parsers on freebase with weak supervision
Chen Liang, Jonathan Berant, Quoc V. Le, Kenneth D. Forbus, and Ni Lao · 2016
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Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, and Tomaso A. Poggio · 2016
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Learning convolutional neural networks for graphs
Mathias Niepert, Mohammed Hassan Ahmed, and Konstantin Kutzkov · 2016
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Compositional learning of embeddings for relation paths in knowledge base and text
Deeppath: A reinforcement learning method for knowledge graph reasoning
Wenhan Xiong, Thien Hoang, and William Yang Wang · 2017
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Differentiable learning of logical rules for knowledge base reasoning
Fan Yang, Zhilin Yang, and William W. Cohen · 2017
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Relational inductive biases, deep learning, and graph networks
Peter W. Battaglia, Jessica B. Hamrick, Victor Bapst, Alvaro Sanchez-Gonzalez, Vinícius Flores Zambaldi, Mateusz Malinowski, Andrea Tacchetti, David Raposo, Adam Santoro, Ryan Faulkner, Çaglar Gülçehre, Francis Song, Andrew J. Ballard, Justin Gilmer, George E. Dahl, Ashish Vaswani, Kelsey R. Allen, Charles Nash, Victoria Langston, Chris Dyer, Nicolas Heess, Daan Wierstra, Pushmeet Kohli, Matthew Botvinick, Oriol Vinyals, Yujia Li, and Razvan Pascanu · 2018
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Variational knowledge graph reasoning
Wenhu Chen, Wenhan Xiong, Xifeng Yan, and William Yang Wang · 2018
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Kristina Toutanova, Victoria Lin, Wen tau Yih, Hoifung Poon, and Chris Quirk · 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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Yoshua Bengio · 2017
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Geometric deep learning: Going beyond euclidean data
Michael M. Bronstein, Joan Bruna, Yann LeCun, Arthur Szlam, and Pierre Vandergheynst · 2017
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Neural message passing for quantum chemistry
Justin Gilmer, Samuel S. Schoenholz, Patrick F. Riley, Oriol Vinyals, and George E. Dahl · 2017
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Vain: Attentional multi-agent predictive modeling
Yedid Hoshen · 2017
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Semi-supervised classification with graph convolutional networks
Thomas N. Kipf and Max Welling · 2017
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Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alexander J. Smola, and Andrew McCallum · 2018
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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel · 2018
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Attention solves your tsp , approximately
Wouter Kool · 2018
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Canonical tensor decomposition for knowledge base completion
Timothée Lacroix, Nicolas Usunier, and Guillaume Obozinski · 2018
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Multi-hop knowledge graph reasoning with reward shaping
Xi Victoria Lin, Richard Socher, and Caiming Xiong · 2018
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A novel embedding model for knowledge base completion based on convolutional neural network
Dai Quoc Nguyen, Tu Dinh Nguyen, Dat Quoc Nguyen, and Dinh Q. Phung · 2018
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Recurrent relational networks
Rasmus Berg Palm, Ulrich Paquet, and Ole Winther · 2018
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Relational recurrent neural networks
Adam Santoro, Ryan Faulkner, David Raposo, Jack W. Rae, Mike Chrzanowski, Théophane Weber, Daan Wierstra, Oriol Vinyals, Razvan Pascanu, and Timothy P. Lillicrap · 2018
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M-walk: Learning to walk over graphs using monte carlo tree search
Yelong Shen, Jianshu Chen, Pu Huang, Yuqing Guo, and Jianfeng Gao · 2018
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Rotate: Knowledge graph embedding by relational rotation in complex space
Zhiqing Sun, Zhi-Hong Deng, Jian-Yun Nie, and Jian Tang · 2018
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Petar Velickovic, Guillem Cucurull, Arantxa Casanova, Alejandro Romero, Pietro Lió, and Yoshua Bengio · 2018
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Knowledge graph reasoning: Recent advances, 2018
William Wang · 2018
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Non-local neural networks
Xiaolong Wang, Ross B. Girshick, Abhinav Gupta, and Kaiming He · 2018
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