Link Prediction On Wordnet
評価指標
Accuracy
評価結果
このベンチマークにおける各モデルのパフォーマンス結果
モデル名 | 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.