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We introduce a relational graph neural network with bi-directional attention mechanism and hierarchical representation learning for open-domain question answering task.
Densely connected convolutional networks
George Forman and Martin Scholz · 2010
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Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto Garcia-Duran, Jason Weston, and Oksana Yakhnenko · 2013
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Adam: Amethod for stochastic optimization
Diederik P Kingma and Jimmy Lei Ba · 2014
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Glove: Global vectors for word representation
Jeffrey Pennington, Richard Socher, and Manning Christopher · 2014
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Dropout: A simple way to prevent neural networks from overfitting
Nitish Srivastava, Geoffrey Hinton, Alex Krizhevsky, Ilya Sutskever, and Ruslan Salakhutdinov · 2014
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Batch normalization: Accelerating deep network training by reducing internal covariate shift
Sergey Ioffe and Christian Szegedy · 2015
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Memory networks
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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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Key-value memory networks for directly reading documents
Alexander Miller, Adam Fisch, Jesse Dodge, Amir-Hossein Karimi, Antoine Bordes, and Jason Weston · 2016
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Holographic embeddings of knowledge graphs
Maximilian Nickel, Lorenzo Rosasco, and Tomaso Poggio · 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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Representation learning of knowledge graphs with entity descriptions
Ruobing Xie, Zhiyuan Liu, Jia Jia, Huanbo Luan, and Maosong Sun · 2016
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Question answering on knowledge bases and text using universal schema and memory networks
Rajarshi Das, Manzil Zaheer, Siva Reddy, and Andrew McCallum · 2017
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Densely connected convolutional networks
Gao Huang, Zhuang Liu, Laurens Van Der Maaten, and Kilian Q Weinberger · 2017
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Glove: Global vectors for word representation
Chen Liang, Jonathan Berant, Quoc Le, Kenneth Forbus, and Ni Lao · 2017
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The more you know: Using knowledge graphs for image classification
Kenneth Marino, Ruslan Salakhutdinov, and Abhinav Gupta · 2017
Graph attention networks
Petar Veličković, Guillem Cucurull, Arantxa Casanova, Pietro Romero, Adriana Liò, and Yoshua Bengio · 2018
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Fvqa: Fact-based visual question answering
Peng Wang, Qi Wu, Chunhua Shen, Anthony Dick, and Anton van den Hengel · 2018
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Hierarchical graph representation learning with differentiable pooling
Zhitao Ying, Jiaxuan You, Christopher Morris, Xiang Ren, Will Hamilton, and Jure Leskovec · 2018
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Link prediction based on graph neural networks
Muhan Zhang and Yixin Chen · 2018
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Variational reasoning for question answering with knowledge graph
Yuyu Zhang, Hanjun Dai, Zornitsa Kozareva, Alexander J Smola, and Le Song · 2018
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Neural natural language inference models enhanced with external knowledge
Qian Chen, Xiaodan Zhu, Zhen-Hua Ling, Diana Inkpen, and Si Wei · 2018
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Out of the box: Reasoning with graph convolution nets for factual visual question answering
Medhini Narasimhan, Svetlana Lazebnik, and Alexander Schwing · 2018
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Open domain question answering using early fusion of knowledge bases and text
Haitian Sun, Bhuwan Dhingra, Manzil Zaheer, Kathryn Mazaitis, Ruslan Salakhutdinov, and William Cohen · 2018
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Ziwei Zhang, Peng Cui, and Wenwu Zhu · 2018
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Graph neural networks: A review of methods and applications
Jie Zhou, Ganqu Cui, Zhengyan Zhang, Cheng Yang, Zhiyuan Liu, and Maosong Sun · 2018
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Augmenting neural machine translation with knowledge graphs
Diego Moussallem, Mihael Arčan, Axel-Cyrille Ngonga Ngomo, and Paul Buitelaar · 2019
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Knowledge-aware graph neural networks with label smoothness regularization for recommender systems
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A comprehensive survey on graph neural networks
Zonghan Wu, Shirui Pan, Fengwen Chen, Guodong Long, Chengqi Zhang, and Philip S Yu · 2019
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