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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 851–900 of 1394 papers

TitleStatusHype
UniHIST: A Unified Framework for Image Restoration With Marginal Histogram Constraints—0
Universal Approximation of Edge Density in Large Graphs—0
Unlocking the Power of Representations in Long-term Novelty-based Exploration—0
Unpacking Information Bottlenecks: Surrogate Objectives for Deep Learning—0
Unpacking Information Bottlenecks: Unifying Information-Theoretic Objectives in Deep Learning—0
Unsupervised Anomaly Detection in MR Images using Multi-Contrast Information—0
Unsupervised Decision Forest for Data Clustering and Density Estimation—0
Unsupervised Distribution Learning for Lunar Surface Anomaly Detection—0
Unsupervised Domain Adaptation for Medical Image Segmentation via Feature-space Density Matching—0
Unsupervised Object Matching for Relational Data—0
Unsupervised Parameter-free Outlier Detection using HDBSCAN* Outlier Profiles—0
Unsupervised Skill Discovery through Skill Regions Differentiation—0
Unsupervised Video Anomaly Detection via Normalizing Flows with Implicit Latent Features—0
Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting—0
VAE-KRnet and its applications to variational Bayes—0
Validation of musculoskeletal segmentation model with uncertainty estimation for bone and muscle assessment in hip-to-knee clinical CT images—0
Variational Auto-Encoder Based Deep Learning Technique For Filling Gaps in Reacting PIV Data—0
Variational Determinant Estimation with Spherical Normalizing Flows—0
Variational Lossy Autoencoder—0
Variational Mixture of Normalizing Flows—0
Verifying the Causes of Adversarial Examples—0
Video prediction using score-based conditional density estimation—0
VQ4ALL: Efficient Neural Network Representation via a Universal Codebook—0
Weakly supervised segment annotation via expectation kernel density estimation—0
WeSpeR: Population spectrum retrieval and spectral density estimation of weighted sample covariance—0
WHAT ARE GANS USEFUL FOR?—0
You are out of context!—0
Fast Multi-Class Probabilistic Classifier by Sparse Non-parametric Density Estimation—0
Fast On-Line Kernel Density Estimation for Active Object Localization—0
Fast optimization of Multithreshold Entropy Linear Classifier—0
Fast rates in statistical and online learning—0
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance—0
Feature Density Estimation for Out-of-Distribution Detection via Normalizing Flows—0
Feature Selection For High-Dimensional Clustering—0
FedBoost: A Communication-Efficient Algorithm for Federated Learning—0
Federated Learning for distribution skewed data using sample weights—0
Feedback Interconnected Mean-Field Density Estimation and Control—0
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions—0
Field Estimation using Robotic Swarms through Bayesian Regression and Mean-Field Feedback—0
Finite Mixture Model of Nonparametric Density Estimation using Sampling Importance Resampling for Persistence Landscape—0
Finite-Sample Bounds for Adaptive Inverse Reinforcement Learning using Passive Langevin Dynamics—0
First Order Locally Orderless Registration—0
FIS-GAN: GAN with Flow-based Importance Sampling—0
Flexible conditional density estimation for time series—0
Flow-based generative models as iterative algorithms in probability space—0
Flow-based Bayesian filtering for high-dimensional nonlinear stochastic dynamical systems—0
Flow-based Self-supervised Density Estimation for Anomalous Sound Detection—0
FlowVocoder: A small Footprint Neural Vocoder based Normalizing flow for Speech Synthesis—0
Food Recommendation With Balancing Comfort and Curiosity—0
From Adaptive Kernel Density Estimation to Sparse Mixture Models—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