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Knowledge graphs (KGs) are powerful in terms of their inference abilities, but are also notorious for their incompleteness and long-tail distribution of relations.
LSTM can solve hard long time lag problems
Sepp Hochreiter and Jürgen Schmidhuber · 1996
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Dimensionality reduction by learning an invariant mapping
Raia Hadsell, Sumit Chopra, and Yann LeCun · 2006
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Yago: a core of semantic knowledge
Fabian M Suchanek, Gjergji Kasneci, and Gerhard Weikum · 2007
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Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor · 2008
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Knowledge graph based search system, June 21 2012
Jeffrey Scott Eder · 2012
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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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Discriminative unsupervised feature learning with convolutional neural networks
Alexey Dosovitskiy, Jost Tobias Springenberg, Martin Riedmiller, and Thomas Brox · 2014
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Wikidata: a free collaborative knowledgebase
Denny Vrandečić and Markus Krötzsch · 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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Information extraction over structured data: Question answering with freebase
Xuchen Yao and Benjamin Van Durme · 2014
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Knowledge graph embedding via dynamic mapping matrix
Guoliang Ji, Shizhu He, Liheng Xu, Kang Liu, and Jun Zhao · 2015
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Learning entity and relation embeddings for knowledge graph completion
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu · 2015
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Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Scott Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng · 2015
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Jimmy Lei Ba, Jamie Ryan Kiros, and Geoffrey E Hinton · 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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Model-agnostic meta-learning for fast adaptation of deep networks
Chelsea Finn, Pieter Abbeel, and Sergey Levine · 2017
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Attention is all you need
One-shot relational learning for knowledge graphs
Wenhan Xiong, Mo Yu, Shiyu Chang, Xiaoxiao Guo, and William Yang Wang · 2018
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Meta relational learning for few-shot link prediction in knowledge graphs
Mingyang Chen, Wen Zhang, Wei Zhang, Qiang Chen, and Huajun Chen · 2019
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Set transformer: A framework for attention-based permutation-invariant neural networks
Juho Lee, Yoonho Lee, Jungtaek Kim, Adam Kosiorek, Seungjin Choi, and Yee Whye Teh · 2019
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Deep graph infomax
Petar Velickovic, William Fedus, William L Hamilton, Pietro Liò, Yoshua Bengio, and R Devon Hjelm · 2019
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Knowledge-aware graph neural networks with label smoothness regularization for recommender systems
Hongwei Wang, Fuzheng Zhang, Mengdi Zhang, Jure Leskovec, Miao Zhao, Wenjie Li, and Zhongyuan Wang · 2019
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Contrastive multi-view representation learning on graphs
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Ashish Vaswani, Noam Shazeer, Niki Parmar, Jakob Uszkoreit, Llion Jones, Aidan N Gomez, Łukasz Kaiser, and Illia Polosukhin · 2017
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Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel · 2018
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Openke: An open toolkit for knowledge embedding
Xu Han, Shulin Cao, Xin Lv, Yankai Lin, Zhiyuan Liu, Maosong Sun, and Juanzi Li · 2018
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Canonical tensor decomposition for knowledge base completion
Timothée Lacroix, Nicolas Usunier, and Guillaume Obozinski · 2018
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Never-ending learning
T. Mitchell, W. Cohen, E. Hruschka, P. Talukdar, B. Yang, J. Betteridge, A. Carlson, B. Dalvi, M. Gardner, B. Kisiel, J. Krishnamurthy, N. Lao, K. Mazaitis, T. Mohamed, N. Nakashole, E. Platanios, A. Ritter, M. Samadi, B. Settles, R. Wang, D. Wijaya, A. Gupta, X. Chen, A. Saparov, M. Greaves, and J. Welling · 2018
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A novel embedding model for knowledge base completion based on convolutional neural network
Tu Dinh Nguyen, Dat Quoc Nguyen, Dinh Phung, et al · 2018
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Infograph: Unsupervised and semi-supervised graph-level representation learning via mutual information maximization
Fan-Yun Sun, Jordan Hoffman, Vikas Verma, and Jian Tang
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Kaveh Hassani and Amir Hosein Khasahmadi · 2020
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Gcc: Graph contrastive coding for graph neural network pre-training
Jiezhong Qiu, Qibin Chen, Yuxiao Dong, Jing Zhang, Hongxia Yang, Ming Ding, Kuansan Wang, and Jie Tang · 2020
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Adaptive attentional network for few-shot knowledge graph completion
Jiawei Sheng, Shu Guo, Zhenyu Chen, Juwei Yue, Lihong Wang, Tingwen Liu, and Hongbo Xu · 2020
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Few-shot knowledge graph completion
Chuxu Zhang, Huaxiu Yao, Chao Huang, Meng Jiang, Zhenhui Li, and Nitesh V Chawla · 2020
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Relational learning with gated and attentive neighbor aggregator for few-shot knowledge graph completion
Guanglin Niu, Yang Li, Chengguang Tang, Ruiying Geng, Jian Dai, Qiao Liu, Hao Wang, Jian Sun, Fei Huang, and Luo Si · 2021
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