Relation operators in knowledge graphs are Kraus channels obeying three axioms, enabling KrausKGE which outperforms baselines on N-to-N relations and supplies a rank-based complexity measure.
Generalizing knowledge graph embedding with universal orthogonal parameterization
2 Pith papers cite this work. Polarity classification is still indexing.
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EC-Net combines Poincare-ball hyperbolic embeddings, hypergraph fusion, and decoupled radial-angular contrastive learning to improve accuracy on multimodal emotion benchmarks especially under partial or noisy modalities.
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Relations Are Channels: Knowledge Graph Embedding via Kraus Decompositions
Relation operators in knowledge graphs are Kraus channels obeying three axioms, enabling KrausKGE which outperforms baselines on N-to-N relations and supplies a rank-based complexity measure.
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Emotion Collider: Dual Hyperbolic Mirror Manifolds for Sentiment Recovery via Anti Emotion Reflection
EC-Net combines Poincare-ball hyperbolic embeddings, hypergraph fusion, and decoupled radial-angular contrastive learning to improve accuracy on multimodal emotion benchmarks especially under partial or noisy modalities.