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Models/B-NAF

B-NAF

Reported on 11 benchmarks across 1 task · 1 paper · 7 SOTA

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

Methodology11 results

  • Density EstimationonUCI GAS
    Log-likelihood· 2019-04-09
    12.06
    SOTA
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonCaltech-101
    NLL· 2019-04-09
    105.42
    SOTA
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonUCI HEPMASS
    Log-likelihood· 2019-04-09
    -14.71
    best: -11.3 (DDE)
    SOTA
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonUCI MINIBOONE
    Log-likelihood· 2019-04-09
    -8.95
    best: -6.94 (DDE)
    SOTA
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonFreyfaces
    NLL· 2019-04-09
    4.42
    SOTA
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonOMNIGLOT
    NLL· 2019-04-09
    100.08
    SOTA
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonUCI POWER
    Log-likelihood· 2019-04-09
    0.61
    best: 1.78 (nMDMA)
    SOTA
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonBSDS300
    Log-likelihood· 2019-04-09
    157.36
    best: 159.8 (TAN)
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonCaltech-101
    Negative ELBO· 2019-04-09
    94.91
    best: 104.03 (FFJORD)
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonFreyfaces
    Negative ELBO· 2019-04-09
    4.33
    best: 4.39 (FFJORD)
    Block Neural Autoregressive FlowarXiv:1904.04676
  • Density EstimationonOMNIGLOT
    Negative ELBO· 2019-04-09
    94.83
    best: 98.33 (FFJORD)
    Block Neural Autoregressive FlowarXiv:1904.04676