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통찰 - Knowledge Graph Completion
Uncertainty-Aware Relational Graph Neural Network for Few-Shot Knowledge Graph Completion Analysis
The author proposes a novel uncertainty-aware few-shot KG completion framework to model uncertainty for better understanding of limited data by learning representations under Gaussian distribution.
HDReason: Algorithm-Hardware Codesign for Hyperdimensional Knowledge Graph Reasoning
Brain-inspired HyperDimensional Computing (HDC) offers an efficient solution for Knowledge Graph Completion (KGC) tasks, leading to improved reasoning accuracy and energy efficiency.
Enhancing Knowledge Graph Completion through Multi-Knowledge Representation Learning
MUSE, a knowledge-aware reasoning model, integrates multi-knowledge representation learning mechanisms, including prior knowledge learning, context message passing, and relational path aggregation, to significantly improve the performance of knowledge graph completion tasks.
