Mohan Timilsina

KGE Calibrator: An Efficient Probability Calibration Method of Knowledge Graph Embedding Models for Trustworthy Link Prediction

Knowledge graph embedding (KGE) models are designed for the task of link prediction, which aims to infer missing triples by learning representations for entities and relations. While KGE models excel at ranking-based link prediction, the critical issue of probability calibration has been largely ove