SOTAVerified

Density Estimation

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.

Source: Contrastive Predictive Coding Based Feature for Automatic Speaker Verification

Papers

Showing 376400 of 1394 papers

TitleStatusHype
Estimating Probability Densities with Transformer and Denoising DiffusionCode0
Estimating Density Models with Truncation Boundaries using Score MatchingCode0
A Triangular Network For Density EstimationCode0
Estimating Feature-Label Dependence Using Gini Distance StatisticsCode0
Evidence Networks: simple losses for fast, amortized, neural Bayesian model comparisonCode0
Anomaly Detection Using Normalizing Flow-Based Density Estimation and Synthetic Defect ClassificationCode0
Density Distribution-based Learning Framework for Addressing Online Continual Learning ChallengesCode0
Enhancing Quantitative Image Synthesis through Pretraining and Resolution Scaling for Bone Mineral Density Estimation from a Plain X-ray ImageCode0
Entropy-Informed Weighting Channel Normalizing FlowCode0
Context-specific kernel-based hidden Markov model for time series analysisCode0
Mixtures of All TreesCode0
ContextFlow++: Generalist-Specialist Flow-based Generative Models with Mixed-Variable Context EncodingCode0
Anomaly Detection with Variance Stabilized Density EstimationCode0
Density reconstruction from schlieren images through Bayesian nonparametric modelsCode0
BMD-GAN: Bone mineral density estimation using x-ray image decomposition into projections of bone-segmented quantitative computed tomography using hierarchical learningCode0
AD-DMKDE: Anomaly Detection through Density Matrices and Fourier FeaturesCode0
Efficient Mixture Learning in Black-Box Variational InferenceCode0
Bone mineral density estimation from a plain X-ray image by learning decomposition into projections of bone-segmented computed tomographyCode0
Asymmetric Variational AutoencodersCode0
MultiplexNet: Towards Fully Satisfied Logical Constraints in Neural NetworksCode0
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian InferenceCode0
Boosted Generative ModelsCode0
Multi-Resolution Continuous Normalizing FlowsCode0
Structured Recognition for Generative Models with Explaining AwayCode0
Efficient and principled score estimation with Nyström kernel exponential familiesCode0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MAFLog-likelihood (nats)3,049Unverified
2DDPMNLL (bits/dim)3.69Unverified
3MRCNFNLL (bits/dim)3.54Unverified
4FFJORDNLL (bits/dim)3.4Unverified
5RNODENLL (bits/dim)3.38Unverified
6Pixel CNNNLL (bits/dim)3.03Unverified
7score SDENLL (bits/dim)2.99Unverified
8Flow matchingNLL (bits/dim)2.99Unverified
9Pixel CNN ++NLL (bits/dim)2.92Unverified
10Image TransformerNLL (bits/dim)2.9Unverified
#ModelMetricClaimedVerifiedStatus
1DVP-VAENLL77.1Unverified
2PaddingFlowMMD-L211Unverified
3FFJORDNLL (bits/dim)0.99Unverified
4RNODENLL (bits/dim)0.97Unverified
5IdentityNLL (bits/dim)0.13Unverified
6MADE MoGLog-likelihood (nats)-1,038.5Unverified
#ModelMetricClaimedVerifiedStatus
1nMDMALog-likelihood1.78Unverified
2DDELog-likelihood0.97Unverified
3B-NAFLog-likelihood0.61Unverified
4FFJORDLog-likelihood0.46Unverified
5MADE MoGLog-likelihood0.4Unverified
6PaddingFlowCD0.14Unverified
#ModelMetricClaimedVerifiedStatus
1TANLog-likelihood159.8Unverified
2FFJORDLog-likelihood157.4Unverified
3B-NAFLog-likelihood157.36Unverified
4MADE MoGLog-likelihood153.71Unverified
5PaddingFlowCD0.5Unverified
#ModelMetricClaimedVerifiedStatus
1GlowNLL (bits/dim)4.09Unverified
2Image TransformerNLL (bits/dim)3.77Unverified
3VDMNLL (bits/dim)3.72Unverified
4i-DODENLL (bits/dim)3.69Unverified
5MuLANNLL (bits/dim)3.67Unverified
#ModelMetricClaimedVerifiedStatus
1B-NAFLog-likelihood12.06Unverified
2DDELog-likelihood9.73Unverified
3FFJORDLog-likelihood8.59Unverified
4MADE MoGLog-likelihood8.47Unverified
5PaddingFlowCD0.89Unverified
#ModelMetricClaimedVerifiedStatus
1PaddingFlowCD13.8Unverified
2DDELog-likelihood-11.3Unverified
3B-NAFLog-likelihood-14.71Unverified
4FFJORDLog-likelihood-14.92Unverified
5MADE MoGLog-likelihood-15.15Unverified
#ModelMetricClaimedVerifiedStatus
1PaddingFlowCD24.5Unverified
2DDELog-likelihood-6.94Unverified
3B-NAFLog-likelihood-8.95Unverified
4FFJORDLog-likelihood-10.43Unverified
5MADE MoGLog-likelihood-12.27Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO98.33Unverified
2B-NAFNegative ELBO94.83Unverified
3DVp-VAENLL89.07Unverified
4PaddingFlowMMD-L220.3Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO104.03Unverified
2B-NAFNegative ELBO94.91Unverified
3PaddingFlowMMD-L217.9Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO4.39Unverified
2B-NAFNegative ELBO4.33Unverified
3PaddingFlowMMD-L20.62Unverified
#ModelMetricClaimedVerifiedStatus
1RNODELog-likelihood1.04Unverified
#ModelMetricClaimedVerifiedStatus
1MAFLog-likelihood5,872Unverified
#ModelMetricClaimedVerifiedStatus
1RNODELog-likelihood3.83Unverified