A curated collection of research on knowledge graphs
Knowledge Base Reasoning with Convolutional-based Recurrent Neural Networks. TKDE 2019. Zhu et al.. [Paper]
DRUM: End-To-End Differentiable Rule Mining On Knowledge Graphs. NeurIPS 2019. Ali Sadeghian, Mohammadreza Armandpour, Patrick Ding, Daisy Zhe Wang. [Paper] [Code]
Chain of Reasoning for Visual Question Answering. NIPS 2018. Wu, Chenfei and Liu, Jinlai and Wang, Xiaojie and Dong, Xuan. [Paper]
Out of the Box: Reasoning with Graph Convolution Nets for Factual Visual Question Answering. NIPS 2018. Medhini Narasimhan, Svetlana Lazebnik, Alex Schwing. [Paper]
Symbolic Graph Reasoning Meets Convolutions. NIPS 2018. Xiaodan Liang, Zhiting HU, Hao Zhang, Liang Lin, and Eric P. Xing. [Paper]
Variational Knowledge Graph Reasoning. NAACL-HLT 2018. Wenhu Chen, Wenhan Xiong, Xifeng Yan, William Yang Wang. [Paper]
DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning. EMNLP 2017. Wenhan Xiong, Thien Hoang, William Yang Wang. [Paper] [Code]
Neural Symbolic Machines: Learning Semantic Parsers on Freebase with Weak Supervision. ACL 2017. Liang, Chen and Berant, Jonathan and Le, Quoc and Forbus, Kenneth D and Lao, Ni. [Paper]
Efficient Inference and Learning in a Large Knowledge Base: Reasoning with Extracted Information using a Locally Groundable First-Order Probabilistic Logic. MLJ 2015. William Yang Wang, Kathryn Mazaitis, Ni Lao, William W. Cohen. [Paper] [Code]
Reasoning with neural tensor networks for knowledge base completion. NIPS 2013. Socher, Richard and Chen, Danqi and Manning, Christopher D and Ng, Andrew. [Paper]
Probabilistic reasoning via deep learning: Neural association models. arXiv 2016. Liu, Quan and Jiang, Hui and Evdokimov, Andrew and Ling, Zhen-Hua and Zhu, Xiaodan and Wei, Si and Hu, Yu. [Paper]
Chains of Reasoning over Entities, Relations, and Text using Recurrent Neural Networks. EACL 2017. Das, Rajarshi and Neelakantan, Arvind and Belanger, David and McCallum, Andrew. [Paper] [Code]
Differentiable learning of logical rules for knowledge base reasoning. NIPS 2017. Yang, Fan and Yang, Zhilin and Cohen, William W. [Paper]
Go for a walk and arrive at the answer: Reasoning over paths in knowledge bases using reinforcement learning. ICLR 2017. Das, Rajarshi and Dhuliawala, Shehzaad and Zaheer, Manzil and Vilnis, Luke and Durugkar, Ishan and Krishnamurthy, Akshay and Smola, Alex and McCallum, Andrew. [Paper]
Iteratively Learning Embeddings and Rules for Knowledge Graph Reasoning. WWW 2019. Zhang, Wen and Paudel, Bibek and Wang, Liang and Chen, Jiaoyan and Zhu, Hai and Zhang, Wei and Bernstein, Abraham and Chen, Huajun. [Paper]
Variational reasoning for question answering with knowledge graph. AAAI 2018. Zhang, Yuyu and Dai, Hanjun and Kozareva, Zornitsa and Smola, Alexander J and Song, Le. [Paper]
The winograd schema challenge. Thirteenth International Conference on the Principles of Knowledge Representation and Reasoning 2012. Levesque, Hector and Davis, Ernest and Morgenstern, Leora. [Paper]
Straight to the facts: Learning knowledge base retrieval for factual visual question answering. ECCV 2018. Narasimhan, Medhini and Schwing, Alexander G. [Paper]
Inferring and executing programs for visual reasoning. ICCV 2017. Johnson, Justin and Hariharan, Bharath and van der Maaten, Laurens and Hoffman, Judy and Fei-Fei, Li and Lawrence Zitnick, C and Girshick, Ross. [Paper]
End-to-end differentiable proving. NIPS 2017. Rocktäschel, Tim and Riedel, Sebastian. [Paper]