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 10261050 of 1394 papers

TitleStatusHype
Outlier Detection in High Dimensional Data0
Out-of-Distribution Detection of Melanoma using Normalizing Flows0
Out-of-distribution detection using normalizing flows on the data manifold0
Overcoming Catastrophic Forgetting with Gaussian Mixture Replay0
High-Dimensional Non-Parametric Density Estimation in Mixed Smooth Sobolev Spaces0
Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders0
Parallel Multiscale Autoregressive Density Estimation0
Parameter and density estimation from real-world traffic data: A kinetic compartmental approach0
Parametric Copula-GP model for analyzing multidimensional neuronal and behavioral relationships0
Parametric Density Estimation with Uncertainty using Deep Ensembles0
Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost0
PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds0
PEDENet: Image Anomaly Localization via Patch Embedding and Density Estimation0
Performance analysis for L\_2 kernel classification0
Permutation invariant functions: statistical tests, density estimation, and computationally efficient embedding0
Towards Theoretical Understandings of Self-Consuming Generative Models0
Persistent Homology for Learning Densities with Bounded Support0
3C-FBI: A Combinatorial method using Convolutions for Circle Fitting in Blurry Images0
A Mathematical Framework for Learning Probability Distributions0
PGNAA Spectral Classification of Metal with Density Estimations0
A marginal sampler for σ-Stable Poisson-Kingman mixture models0
Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images0
Video prediction using score-based conditional density estimation0
A Many-Objective Evolutionary Algorithm with Angle-Based Selection and Shift-Based Density Estimation0
Alternators With Noise Models0
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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