Kun Gao

Kun Gao

He/His

📢 Bio: Researcher at IHPC; Ph.D. from Peking University

🔬 Research topics: Differentiable Inductive Logic Programming; Neuro-Symbolic Methods; Knowledge Representation and Reasoning

Sigificant Publications

A differentiable first-order rule learner for inductive logic programming (Abstract Reprint). Kun Gao, Katsumi Inoue, Yongzhi Cao, and Hanpin Wang (2024). IJCAI-24. (Abstract)
ImageA differentiable first-order rule learner for inductive logic programming. Kun Gao, Katsumi Inoue, Yongzhi Cao, and Hanpin Wang (2024). Artificial Intelligence. (Code) (Paper)
Research on Inductive Logic Programming with Neuro-Symbolic Methods. Kun Gao (2023). Doctoral dissertation, Peking University. (Abstract)
ImageLearning First-Order Rules with Differentiable Logic Program Semantics. Kun Gao, Katsumi Inoue, Yongzhi Cao, and Hanpin Wang (2022). IJCAI-ECAI 2022. (Long Oral Presentation, top 3.5%) (Video) (Code) (Slide) (Paper)
ImageLearning from interpretation transition using differentiable logic programming semantics. Kun Gao, Hanpin Wang, Yongzhi Cao, and Katsumi Inoue (2022). Machine Learning. (Video) (Code) (Slide) (Paper)