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Explainable Reasoning

  • SAFRAN: An interpretable, rule-based link prediction method outperforming embedding models (AKBC 2021)

  • Explainable Biomedical Recommendations via Reinforcement Learning Reasoning on Knowledge Graphs (Arxiv 2021)

    • Gavin Edwards, Sebastian Nilsson, Benedek Rozemberczki, Eliseo Papa
    • [Paper]

  • Complex Query Answering with Neural Link Predictors (ICLR 2021, Outstanding Paper Award)

    • Erik Arakelyan, Daniel Daza, Pasquale Minervini, Michael Cochez
    • [Paper]
    • [Code]

  • CogKR: Cognitive Graph for Multi-hop Knowledge Reasoning (TKDE 2021)

    • Zhengxiao Du, Chang Zhou, Jiangchao Yao, Teng Tu, Letian Cheng, Hongxia Yang, Jingren Zhou, Jie Tang
    • [Paper]
    • [Code]

  • Is Multi-Hop Reasoning Really Explainable? Towards Benchmarking Reasoning Interpretability (Arxiv 2021)

    • Xin Lv, Yixin Cao, Lei Hou, Juanzi Li, Zhiyuan Liu, Yichi Zhang, Zelin Dai
    • [Paper]
    • [Code]

  • Neural Multi-Hop Reasoning With Logical Rules on Biomedical Knowledge Graphs (ESWC 2021)

    • Yushan Liu, Marcel Hildebrandt, Mitchell Joblin, Martin Ringsquandl, Rime Raissouni, Volker Tresp
    • [Paper]
    • [Code]

  • Learning Reasoning Strategies in End-to-End Differentiable Proving (ICML 2020)

    • Pasquale Minervini, Sebastian Riedel, Pontus Stenetorp, Edward Grefenstette, Tim Rocktäschel
    • [Paper]
    • [Code]

  • Leveraging Demonstrations for Reinforcement Recommendation Reasoning over Knowledge Graphs (SIGIR 2020)

    • Kangzhi Zhao Xiting Wang Yuren Zhang Li Zhao Zheng Liu Chunxiao Xing Xing Xie
    • [Paper]

  • Neural Symbolic Reasoning on Knowledge Graph: RuleGuider (EMNLP 2020)

    • Deren Lei, Gangrong Jiang, Xiaotao Gu, Kexuan Sun, Yuning Mao, Xiang Ren
    • [Paper]
    • [Code]

  • Differentiable Reasoning on Large Knowledge Bases and Natural Language (AAAI 2020, Oral)

    • Pasquale Minervini, Matko Bosnjak, Tim Rocktäschel, Sebastian Riedel, Edward Grefenstette
    • [Paper]
    • [Code]

  • Reinforcement Knowledge Graph Reasoning for Explainable Recommendation (SIGIR 2019)

    • Yikun Xian, Zuohui Fu, S. Muthukrishnan, Gerard de Melo, Yongfeng Zhang
    • [Paper]
    • [Code]

  • Anytime Bottom-Up Rule Learning for Knowledge Graph Completion (IJCAI 2019)

    • Christian Meilicke, Melisachew Wudage Chekol, Daniel Ruffinell, Heiner Stuckenschmidt
    • [Paper]
    • [Code]

  • M-Walk: Learning to Walk over Graphs using Monte Carlo Tree Search (NeurIPS 2018)

    • Yelong Shen, Jianshu Chen, Po-Sen Huang, Yuqing Guo, Jianfeng Gao
    • [Paper]

  • Go for a Walk and Arrive at the Answer - Reasoning over Paths in Knowledge Bases using Reinforcement Learning (ICLR 2018)

    • Rajarshi Das, Shehzaad Dhuliawala, Manzil Zaheer, Luke Vilnis, Ishan Durugkar, Akshay Krishnamurthy, Alex Smola, Andrew McCallum
    • [Paper]
    • [Code]

  • DeepPath: A Reinforcement Learning Method for Knowledge Graph Reasoning (EMNLP 2017)