Fetching the paper…
Reading the bibliography…
Knowledge graphs (KGs) facilitate a wide variety of applications.
Recurrent event network: Autoregressive structure inference over temporal knowledge graphs
Woojeong Jin, Meng Qu, Xisen Jin, and Xiang Ren. 2019 · 1904
Earlier work this paper cites.
Freebase: a collaboratively created graph database for structuring human knowledge
Kurt Bollacker, Colin Evans, Praveen Paritosh, Tim Sturge, and Jamie Taylor. 2008 · 2008
Earlier work this paper cites.
Toward an architecture for never-ending language learning
Andrew Carlson, Justin Betteridge, Bryan Kisiel, Burr Settles, Estevam R Hruschka, and Tom M Mitchell. 2010 · 2010
Earlier work this paper cites.
Translating embeddings for modeling multi-relational data
Antoine Bordes, Nicolas Usunier, Alberto García-Durán, Jason Weston, and Oksana Yakhnenko. 2013 · 2013
Earlier work this paper cites.
Knowledge base completion via search-based question answering
Robert West, Evgeniy Gabrilovich, Kevin Murphy, Shaohua Sun, Rahul Gupta, and Dekang Lin. 2014 · 2014
Earlier work this paper cites.
Learning entity and relation embeddings for knowledge graph completion
Yankai Lin, Zhiyuan Liu, Maosong Sun, Yang Liu, and Xuan Zhu. 2015 · 2015
Earlier work this paper cites.
Observed versus latent features for knowledge base and text inference
Kristina Toutanova and Danqi Chen. 2015 · 2015
Earlier work this paper cites.
Representing text for joint embedding of text and knowledge bases
Kristina Toutanova, Danqi Chen, Patrick Pantel, Hoifung Poon, Pallavi Choudhury, and Michael Gamon. 2015 · 2015
Earlier work this paper cites.
Embedding entities and relations for learning and inference in knowledge bases
Bishan Yang, Wen-tau Yih, Xiaodong He, Jianfeng Gao, and Li Deng. 2015 · 2015
Earlier work this paper cites.
Neural architecture search with reinforcement learning
Barret Zoph and Quoc V Le. 2016 · 2016
Earlier work this paper cites.
Deeppath: A reinforcement learning method for knowledge graph reasoning
Wenhan Xiong, Thien Hoang, and William Yang Wang. 2017b · 2017
Earlier work this paper cites.
Convolutional 2d knowledge graph embeddings
Tim Dettmers, Pasquale Minervini, Pontus Stenetorp, and Sebastian Riedel. 2018 · 2018
Cited alongside, same era.
Learning sequence encoders for temporal knowledge graph completion
Alberto García-Durán, Sebastijan Dumančić, and Mathias Niepert. 2018 · 2018
Cited alongside, same era.
Modeling relational data with graph convolutional networks
Michael Schlichtkrull, Thomas N Kipf, Peter Bloem, Rianne Van Den Berg, Ivan Titov, and Max Welling. 2018 · 2018
Cited alongside, same era.
Graph convolutional neural networks for web-scale recommender systems
Rex Ying, Ruining He, Kaifeng Chen, Pong Eksombatchai, William L Hamilton, and Jure Leskovec. 2018 · 2018
Cited alongside, same era.
Graph neural networks for social recommendation
Wenqi Fan, Yao Ma, Qing Li, Yuan He, Eric Zhao, Jiliang Tang, and Dawei Yin. 2019 · 2019
Cited alongside, same era.
Graph condensation for graph neural networks
Wei Jin, Lingxiao Zhao, Shichang Zhang, Yozen Liu, Jiliang Tang, and Neil Shah. 2021 · 2021
Later among the works it cites.
Hanxiao Liu, Zihang Dai, David R So, and Quoc V Le. 2021 · 2021
Later among the works it cites.
A unified view on graph neural networks as graph signal denoising
Yao Ma, Xiaorui Liu, Tong Zhao, Yozen Liu, Jiliang Tang, and Neil Shah. 2021 · 2021
Later among the works it cites.
Mlp-mixer: An all-mlp architecture for vision
Ilya Tolstikhin, Neil Houlsby, Alexander Kolesnikov, Lucas Beyer, Xiaohua Zhai, Thomas Unterthiner, Jessica Yung, Daniel Keysers, Jakob Uszkoreit, Mario Lucic, et al. 2021 · 2021
Later among the works it cites.
Knowledge embedding based graph convolutional network
Donghan Yu, Yiming Yang, Ruohong Zhang, and Yuexin Wu. 2021 · 2021
alphaXiv searches the wider corpus for related work and actual follow-ups.
alphaXiv is searching for related work…
Learning attention-based embeddings for relation prediction in knowledge graphs
Deepak Nathani, Jatin Chauhan, Charu Sharma, and Manohar Kaul. 2019 · 2019
Cited alongside, same era.
Kgat: Knowledge graph attention network for recommendation
Xiang Wang, Xiangnan He, Yixin Cao, Meng Liu, and Tat-Seng Chua. 2019 · 2019
Cited alongside, same era.
A vectorized relational graph convolutional network for multi-relational network alignment
Rui Ye, Xin Li, Yujie Fang, Hongyu Zang, and Mingzhong Wang. 2019 · 2019
Cited alongside, same era.
A re-evaluation of knowledge graph completion methods
Zhiqing Sun, Shikhar Vashishth, Soumya Sanyal, Partha Talukdar, and Yiming Yang. 2020 · 2020
Cited alongside, same era.
Composition-based multi-relational graph convolutional networks
Shikhar Vashishth, Soumya Sanyal, Vikram Nitin, and Partha P. Talukdar. 2020 · 2020
Cited alongside, same era.
Explicit semantic ranking for academic search via knowledge graph embedding
Chenyan Xiong, Russell Power, and Jamie Callan. 2017a
Cited in the paper.
Graph-less neural networks: Teaching old mlps new tricks via distillation
Shichang Zhang, Yozen Liu, Yizhou Sun, and Neil Shah. 2022a
Cited in the paper.
Later among the works it cites.
Neural bellman-ford networks: A general graph neural network framework for link prediction
Zhaocheng Zhu, Zuobai Zhang, Louis-Pascal Xhonneux, and Jian Tang. 2021 · 2021
Later among the works it cites.
Knowledge graph reasoning with relational digraph
Yongqi Zhang and Quanming Yao. 2022 · 2022
Closest in time.
Rethinking graph convolutional networks in knowledge graph completion
Zhanqiu Zhang, Jie Wang, Jieping Ye, and Feng Wu. 2022b · 2022
Closest in time.
From stars to subgraphs: Uplifting any gnn with local structure awareness
Lingxiao Zhao, Wei Jin, Leman Akoglu, and Neil Shah. 2022 · 2022
Closest in time.
Learning to efficiently propagate for reasoning on knowledge graphs
Zhaocheng Zhu, Xinyu Yuan, Louis-Pascal Xhonneux, Ming Zhang, Maxime Gazeau, and Jian Tang. 2022 · 2022
Closest in time.