Link Property Prediction On Ogbl Biokg
評価指標
Number of params
Test MRR
Validation MRR
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
比較表
| モデル名 | Number of params | Test MRR | Validation MRR |
|---|---|---|---|
| relation-prediction-as-an-auxiliary-training | 187750000 | 0.8494 | 0.8497 |
| モデル 2 | 187648000 | 0.7452 ± 0.0004 | 0.7456 ± 0.0003 |
| complex-embeddings-for-simple-link-prediction | 187648000 | 0.8095 ± 0.0007 | 0.8105 ± 0.0001 |
| embedding-knowledge-graphs-attentive-to | - | 0.9011 | 0.9011 |
| embedding-entities-and-relations-for-learning | 187648000 | 0.8043 ± 0.0003 | 0.8055 ± 0.0003 |
| how-to-turn-your-knowledge-graph-embeddings-1 | 187648000 | 0.8583 ± 0.0005 | 0.8592 ± 0.0004 |
| モデル 7 | 187750000 | 0.8492 ± 0.0002 | 0.8497 ± 0.0002 |
| モデル 8 | 187648000 | 0.8583 ± 0.0005 | 0.8592 ± 0.0004 |
| prior-bilinear-based-models-for-knowledge | 181654170 | 0.8550 ± 0.0003 | 0.8553 ± 0.0001 |
| relation-aware-ensemble-learning-for | 849427106 | 0.9618 ± 0.0002 | 0.9627 ± 0.0004 |
| autosf-towards-automatic-scoring-function | 192047104 | 0.8536 ± 0.0003 | 0.8548 ± 0.0002 |
| autokge-searching-scoring-functions-for | 93824000 | 0.8309 ± 0.0008 | 0.8317 ± 0.0007 |
| pairre-knowledge-graph-embeddings-via-paired | 187750000 | 0.8164 ± 0.0005 | 0.8172 ± 0.0005 |
| neural-bellman-ford-networks-a-general-graph | 734,209 | 0.8317 | 0.8318 |
| モデル 15 | 469630002 | 0.8348 ± 0.0007 | 0.8360 ± 0.0006 |
| rotate-knowledge-graph-embedding-by | 187597000 | 0.7989 ± 0.0004 | 0.7997 ± 0.0002 |