Collaborative Filtering On Movielens 1M
Métriques
RMSE
Résultats
Résultats de performance de divers modèles sur ce benchmark
Tableau comparatif
| Nom du modèle | RMSE |
|---|---|
| a-neural-autoregressive-approach-to | 0.829 |
| neural-network-matrix-factorization | 0.843 |
| bert4rec-sequential-recommendation-with | - |
| behavior-sequence-transformer-for-e-commerce | 0.8401 |
| graph-convolutional-matrix-completion | 0.832 |
| fedgnn-federated-graph-neural-network-for | 0.848 |
| session-based-recommendations-with-recurrent | - |
| sse-pt-sequential-recommendation-via | - |
| deep-models-of-interactions-across-sets | 0.860 |
| sequential-variational-autoencoders-for | - |
| 180809781 | - |
| a-federated-graph-neural-network-framework | 0.839 |
| dictionary-learning-for-massive-matrix | 0.866 |
| infinite-recommendation-networks-a-data | - |
| svd-ae-simple-autoencoders-for-collaborative | - |
| hybrid-recommender-system-based-on | 0.8574 |
| latent-relational-metric-learning-via-memory | - |
| autorec-autoencoders-meet-collaborative | 0.831 |
| inductive-graph-pattern-learning-for | 0.857 |
| actions-speak-louder-than-words-trillion | - |
| hyperbolic-recommender-systems | - |
| ghrs-graph-based-hybrid-recommendation-system | 0.838 |
| collaborative-metric-learning | - |
| kernelized-synaptic-weight-matrices | 0.824 |
| unifying-knowledge-graph-learning-and | - |
| glocal-k-global-and-local-kernels-for | 0.8227 |
| hybrid-recommender-system-based-on | 0.8321 |
| inductive-matrix-completion-using-graph | 0.829 |
| context-aware-compilation-of-dnn-training | - |
| explainable-knowledge-graph-based | - |
| efficient-retrieval-with-learned-similarities | - |