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Knowledge Graph Reasoning at Scale

Primary supervisor

Shirui Pan

Knowledge graphs are important tools to enable next generation AI through providing explanation for different applications such as question answering. Knowledge graphs are typically sparse, noisy, and incomplete. Knowledge graph reasoning aims to solving this problem by reasoning missing facts from the large scale knowledge base. This project aims to develop novel scalable technique for knowledge graph reasoning. The developed techniques will be further generalised to more general graphs with graph neural networks. 

Required knowledge

Graph Neural Networks

Knowledge graphs

Project funding

Project based scholarship

Learn more about minimum entry requirements.