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Unconditional Density Estimation on HEPMASS (test)

14.01NLL (nats)RQ-NSF (AR)
13.586816.443419.322.1566Oct 2, 2018Jan 16, 2019May 2, 2019Aug 17, 2019Dec 1, 2019Mar 16, 2020Jul 1, 2020

Evaluation results

MethodLinks
RQ-NSF (AR)Training Approach=Maximum Likelihood2020.0714.01—
FFJORD2018.1014.92—
FFJORD2018.1014.92—
FFJORDTraining Approach=Maximum Likelihood2020.0714.92—
MAF-DDSF2018.1015.09—
MAF-DDSF2018.1015.09—
TAN2018.1015.12—
TAN2018.1015.12—
MAFTraining Approach=Maximum Likelihood2020.0717.39—
GFTraining Approach=Maximum Likelihood2020.0717.59—
MAF2018.1017.7—
MAF2018.1017.7—
Real NVP2018.1018.71—
Real NVP2018.1018.71—
Real NVPTraining Approach=Maximum Likelihood2020.0718.71—
Glow2018.1018.92—
Glow2018.1018.92—
GlowTraining Approach=Maximum Likelihood2020.0718.92—
GISTraining Approach=Iterative2020.0719—
MADE2018.1020.98—
MADE2018.1020.98—
RBIGTraining Approach=Iterative2020.0724.59—
DDE (Ours)Normalization Strategy=Sampling, sigma_n=0.022020.01—-11.3
De Cao et al. (2019)Normalization Strategy=Sampling2020.01—-14.71
Dinh et al. (2017)Normalization Strategy=Analytical2020.01—-18.71
Gaussian2017.05—-27.93
Germain et al. (2015)Normalization Strategy=Analytical, Mixture of Gaussians=true2020.01—-15.15
Grathwohl et al. (2019)Normalization Strategy=Analytical2020.01—-14.92
Huang et al. (2018)Normalization Strategy=Analytical2020.01—-15.09
Kingma and Dhariwal (2018)Normalization Strategy=Analytical2020.01—-18.92
MADE2017.05—-20.98
MADE MoGOutput distribution=Mixture of Gaussians2017.05—-15.15
MAFNumber of layers=52017.05—-17.7
MAFNumber of layers=102017.05—-17.73
MAF MoGNumber of layers=5, Output distribution=Mixture of Gaussians2017.05—-17.39
Oliva et al. (2018)Normalization Strategy=Analytical2020.01—-13.78
Papamakarios et al. (2017)Normalization Strategy=Analytical2020.01—-17.73
Papamakarios et al. (2017)Normalization Strategy=Analytical, Mixture of Gaussians=true2020.01—-17.39
Real NVPNumber of layers=52017.05—-19.62
Real NVPNumber of layers=102017.05—-18.71