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Models/RecVAE

RecVAE

Reported on 9 benchmarks across 1 task · 1 paper · 1 SOTA

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

Knowledge Base9 results

  • Recommendation SystemsonMovieLens 20M
    Recall@50· 2019-12-24
    0.553
    SOTA
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160
  • Recommendation SystemsonMovieLens 20M
    Recall@20· 2019-12-24
    0.414
    best: 0.418 (Multi-Gradient Descent)
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160
  • Recommendation SystemsonMovieLens 20M
    nDCG@100· 2019-12-24
    0.442
    best: 0.448 (VASP)
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160
  • Recommendation SystemsonMillion Song Dataset
    Recall@20· 2019-12-24
    0.276
    best: 0.333 (EASE)
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160
  • Recommendation SystemsonMillion Song Dataset
    Recall@50· 2019-12-24
    0.374
    best: 0.428 (EASE)
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160
  • Recommendation SystemsonMillion Song Dataset
    nDCG@100· 2019-12-24
    0.326
    best: 0.389 (EASE)
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160
  • Recommendation SystemsonNetflix
    Recall@20· 2019-12-24
    0.361
    best: 0.37678 (H+Vamp Gated)
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160
  • Recommendation SystemsonNetflix
    Recall@50· 2019-12-24
    0.452
    best: 0.46252 (H+Vamp Gated)
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160
  • Recommendation SystemsonNetflix
    nDCG@100· 2019-12-24
    0.394
    best: 0.40861 (H+Vamp Gated)
    RecVAE: a New Variational Autoencoder for Top-N Recommendations with Implicit FeedbackarXiv:1912.11160