Link Prediction On Wordnet
평가 지표
Accuracy
평가 결과
이 벤치마크에서 각 모델의 성능 결과
모델 이름 | Accuracy | Paper Title | Repository |
|---|---|---|---|
| Poincare Embeddings (dim=10) | 68.3 | Poincaré Embeddings for Learning Hierarchical Representations | - |
| Hyperbolic Entailment Cones | 94.4 | Hyperbolic Entailment Cones for Learning Hierarchical Embeddings | - |
| Hyper-SAGNN-W | - | Hyper-SAGNN: a self-attention based graph neural network for hypergraphs | - |
| Hyper-SAGNN-E | - | Hyper-SAGNN: a self-attention based graph neural network for hypergraphs | - |
| Poincare Embeddings (dim=20) | 74.3 | Poincaré Embeddings for Learning Hierarchical Representations | - |
| Poincare Embeddings (dim=50) | 77.0 | Poincaré Embeddings for Learning Hierarchical Representations | - |
| Poincare Embeddings (dim=100) | 77.4 | Poincaré Embeddings for Learning Hierarchical Representations | - |
0 of 7 row(s) selected.