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Knowledge Representation

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Knowledge Representation

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Research Frontiers in Knowledge Graph Embedding and Link Prediction

Development of vector space representations for entities and relations to predict missing links and infer new knowledge graph connections.

Temporal Dynamics in Evolving Knowledge Graphs
Semantic Collapse in High-Dimensional Embedding Spaces
Cross-Modal Knowledge Graph Alignment and Fusion
Explainability Through Embedding Geometry Decomposition
Rare Relation Prediction in Sparse Knowledge Domains
Adversarial Robustness of Graph Embedding Models
Neural-Symbolic Integration for Link Prediction
Zero-Shot Knowledge Transfer Across Heterogeneous Graphs
Uncertainty Quantification in Embedding-Based Inference
Compositional Reasoning in Learned Relational Spaces

All Knowledge Representation PhD categories