MetaHKG: Meta Hyperbolic Learning for Few-shot Temporal Reasoning - M1.2

Explore a conference talk on MetaHKG, a novel approach to meta hyperbolic learning for few-shot temporal reasoning in knowledge graphs. Delve into the research presented by authors Ruijie Wang, Yutong Zhang, Jinyang Li, and others at the SIGIR 2024 conference. Learn about the innovative techniques used to enhance reasoning capabilities in knowledge graphs with limited data. Gain insights into how hyperbolic geometry is leveraged to improve temporal reasoning tasks. Understand the potential applications and implications of this research for advancing artificial intelligence and machine learning in the field of information retrieval.

SIGIR 2024 M1.2 [fp] MetaHKG: Meta Hyperbolic Learning for Few-shot Temporal Reasoning