CF-NADE

Reported on 2 benchmarks across 1 task · 1 paper · 2 SOTA

Note: results are matched by exact model name. Different papers may use the same name for different model variants.

Knowledge Base2 results

Recommendation SystemsonMovieLens 1M
RMSE· 2016-05-31
0.829
best: 0.8227 (GLocal-K)
SOTA
A Neural Autoregressive Approach to Collaborative Filtering arXiv:1605.09477
Recommendation SystemsonMovieLens 10M
RMSE· 2016-05-31
0.771
best: 0.7485 (Bayesian timeSVD++ flipped)
SOTA
A Neural Autoregressive Approach to Collaborative Filtering arXiv:1605.09477