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

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Showing 151–200 of 1394 papers

TitleStatusHype
Convex Potential Flows: Universal Probability Distributions with Optimal Transport and Convex OptimizationCode1
Free-form Flows: Make Any Architecture a Normalizing FlowCode1
DEGAN: Time Series Anomaly Detection using Generative Adversarial Network Discriminators and Density EstimationCode1
Gaussianizing the Earth: Multidimensional Information Measures for Earth Data AnalysisCode1
Dissimilarity Mixture Autoencoder for Deep ClusteringCode1
Generative Flows with Matrix ExponentialCode1
An efficient manifold density estimator for all recommendation systemsCode1
Glow: Generative Flow with Invertible 1x1 ConvolutionsCode1
Graph Mixture Density NetworksCode1
Equivariant graph neural networks for fast electron density estimation of molecules, liquids, and solidsCode1
Hierarchical Autoregressive Modeling for Neural Video CompressionCode1
Hierarchical Infinite Relational ModelCode1
How to train your neural ODE: the world of Jacobian and kinetic regularizationCode1
Hunting Sparsity: Density-Guided Contrastive Learning for Semi-Supervised Semantic SegmentationCode1
HyperSPNs: Compact and Expressive Probabilistic CircuitsCode1
Importance Weighted AutoencodersCode1
Information Theory Measures via Multidimensional GaussianizationCode1
Interpolation Technique to Speed Up Gradients Propagation in Neural ODEsCode1
Invertible Monotone Operators for Normalizing FlowsCode1
Invertible Residual NetworksCode1
Kernel Methods and their derivatives: Concept and perspectives for the Earth system sciencesCode1
Label-Free Multivariate Time Series Anomaly DetectionCode1
Learning Differential Equations that are Easy to SolveCode1
Learning with Density Matrices and Random FeaturesCode1
A Coupled Flow Approach to Imitation LearningCode1
Graphical Normalizing FlowsCode1
Marginalizable Density ModelsCode1
A sampling-based circuit for optimal decision making—0
Alternators With Noise Models—0
A Local Density-Based Approach for Local Outlier Detection—0
A Robust Framework for Moving-Object Detection and Vehicular Traffic Density Estimation—0
Adaptive Transfer Learning of Multi-View Time Series Classification—0
Compressing Image-to-Image Translation GANs Using Local Density Structures on Their Learned Manifold—0
ARMCMC: ONLINE MODEL PARAMETERS DENSITY ESTIMATION IN BAYESIAN PARADIGM—0
ARMCMC: Online Bayesian Density Estimation of Model Parameters—0
Adaptive Random Bandwidth for Inference in CAViaR Models—0
A Large Contextual Dataset for Classification, Detection and Counting of Cars with Deep Learning—0
About the Cost of Central Privacy in Density Estimation—0
Computational Challenges in Non-parametric Prediction of Bradycardia in Preterm Infants—0
Adaptive learning of density ratios in RKHS—0
A RAD approach to deep mixture models—0
Quasi-Bayesian sequential deconvolution—0
AgRegNet: A Deep Regression Network for Flower and Fruit Density Estimation, Localization, and Counting in Orchards—0
Complete gradient clustering algorithm for features analysis of x-ray images—0
Approximating Hierarchical MV-sets for Hierarchical Clustering—0
Content Reduction, Surprisal and Information Density Estimation for Long Documents—0
Combining local and global smoothing in multivariate density estimation—0
Improving Discrete Latent Representations With Differentiable Approximation Bridges—0
Agnostic Private Density Estimation for GMMs via List Global Stability—0
Combined approach for automatic and robust calculation of dominant frequency of electrogastrogram—0
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All datasetsCIFAR-10MNISTUCI POWERBSDS300ImageNet 32x32UCI GASUCI HEPMASSUCI MINIBOONEOMNIGLOTCaltech-101FreyfacesCelebA-HQ 256x256

Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MAFLog-likelihood (nats)3,049—Unverified
2DDPMNLL (bits/dim)3.69—Unverified
3MRCNFNLL (bits/dim)3.54—Unverified
4FFJORDNLL (bits/dim)3.4—Unverified
5RNODENLL (bits/dim)3.38—Unverified
6Pixel CNNNLL (bits/dim)3.03—Unverified
7Flow matchingNLL (bits/dim)2.99—Unverified
8score SDENLL (bits/dim)2.99—Unverified
9Pixel CNN ++NLL (bits/dim)2.92—Unverified
10Image TransformerNLL (bits/dim)2.9—Unverified
#ModelMetricClaimedVerifiedStatus
1DVP-VAENLL77.1—Unverified
2PaddingFlowMMD-L211—Unverified
3FFJORDNLL (bits/dim)0.99—Unverified
4RNODENLL (bits/dim)0.97—Unverified
5IdentityNLL (bits/dim)0.13—Unverified
6MADE MoGLog-likelihood (nats)-1,038.5—Unverified
#ModelMetricClaimedVerifiedStatus
1nMDMALog-likelihood1.78—Unverified
2DDELog-likelihood0.97—Unverified
3B-NAFLog-likelihood0.61—Unverified
4FFJORDLog-likelihood0.46—Unverified
5MADE MoGLog-likelihood0.4—Unverified
6PaddingFlowCD0.14—Unverified
#ModelMetricClaimedVerifiedStatus
1TANLog-likelihood159.8—Unverified
2FFJORDLog-likelihood157.4—Unverified
3B-NAFLog-likelihood157.36—Unverified
4MADE MoGLog-likelihood153.71—Unverified
5PaddingFlowCD0.5—Unverified
#ModelMetricClaimedVerifiedStatus
1GlowNLL (bits/dim)4.09—Unverified
2Image TransformerNLL (bits/dim)3.77—Unverified
3VDMNLL (bits/dim)3.72—Unverified
4i-DODENLL (bits/dim)3.69—Unverified
5MuLANNLL (bits/dim)3.67—Unverified
#ModelMetricClaimedVerifiedStatus
1B-NAFLog-likelihood12.06—Unverified
2DDELog-likelihood9.73—Unverified
3FFJORDLog-likelihood8.59—Unverified
4MADE MoGLog-likelihood8.47—Unverified
5PaddingFlowCD0.89—Unverified
#ModelMetricClaimedVerifiedStatus
1PaddingFlowCD13.8—Unverified
2DDELog-likelihood-11.3—Unverified
3B-NAFLog-likelihood-14.71—Unverified
4FFJORDLog-likelihood-14.92—Unverified
5MADE MoGLog-likelihood-15.15—Unverified
#ModelMetricClaimedVerifiedStatus
1PaddingFlowCD24.5—Unverified
2DDELog-likelihood-6.94—Unverified
3B-NAFLog-likelihood-8.95—Unverified
4FFJORDLog-likelihood-10.43—Unverified
5MADE MoGLog-likelihood-12.27—Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO98.33—Unverified
2B-NAFNegative ELBO94.83—Unverified
3DVp-VAENLL89.07—Unverified
4PaddingFlowMMD-L220.3—Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO104.03—Unverified
2B-NAFNegative ELBO94.91—Unverified
3PaddingFlowMMD-L217.9—Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO4.39—Unverified
2B-NAFNegative ELBO4.33—Unverified
3PaddingFlowMMD-L20.62—Unverified
#ModelMetricClaimedVerifiedStatus
1RNODELog-likelihood1.04—Unverified
#ModelMetricClaimedVerifiedStatus
1MAFLog-likelihood5,872—Unverified
#ModelMetricClaimedVerifiedStatus
1RNODELog-likelihood3.83—Unverified