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Biquaternionic Space with Complex-valued Attention for Temporal Knowledge Graph Completion

Geng, Rushan et al.
arXiv (OAI Expanded) · Papers
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artificial-intelligencemachine-learning
Temporal knowledge graph embedding (TKGE) models infer missing facts in knowledge graphs that evolve over time. Many existing models use a single geometric space, which can limit their ability to represent diverse relational patterns, or treat entity representations as static. We propose Biquaternio
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