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SotA/Methodology/Density Estimation

Density Estimation

52 benchmarks1394 papers

The goal of Density Estimation is to give an accurate description of the underlying probabilistic density distribution of an observable data set with unknown density.

<span class="description-source">Source: Contrastive Predictive Coding Based Feature for Automatic Speaker Verification </span>

Benchmarks

Density Estimation on CIFAR-10

NLL (bits/dim)Log-likelihood (nats)

Density Estimation on ImageNet 32x32

NLL (bits/dim)

Density Estimation on UCI POWER

Log-likelihoodCDEMDMMD-CDMMD-EMDNLL

Density Estimation on BSDS300

Log-likelihoodCDEMDMMD-CDMMD-EMDNLL

Density Estimation on UCI GAS

Log-likelihoodCDEMDMMD-CDMMD-EMD

Density Estimation on UCI HEPMASS

Log-likelihoodCDEMDMMD-CDMMD-EMDNLL

Density Estimation on UCI MINIBOONE

Log-likelihoodNLLCDEMDMMD-CDMMD-EMD

Density Estimation on MNIST

NLL (bits/dim)MMD-L2Log-likelihood (nats)NLLCOV-L2

Density Estimation on Caltech-101

Negative ELBOMMD-L2NLLCOV-L2

Density Estimation on Freyfaces

Negative ELBOMMD-L2NLLCOV-L2

Density Estimation on OMNIGLOT

Negative ELBONLLMMD-L2COV-L2

Density Estimation on CIFAR-10 (Conditional)

Log-likelihood

Density Estimation on CelebA-HQ 256x256

Log-likelihood

Density Estimation on ImageNet 64x64

Log-likelihood