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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 901–950 of 1394 papers

TitleStatusHype
Multiclass histogram-based thresholding using kernel density estimation and scale-space representations—0
Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport—0
TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models—0
Multiple-policy Evaluation via Density Estimation—0
Multiple Reflection Symmetry Detection via Linear-Directional Kernel Density Estimation—0
A Discriminative Technique for Multiple-Source Adaptation—0
Unsupervised Distribution Learning for Lunar Surface Anomaly Detection—0
Unsupervised Domain Adaptation for Medical Image Segmentation via Feature-space Density Matching—0
TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation—0
Multi-Scale Architectures Matter: On the Adversarial Robustness of Flow-based Lossless Compression—0
Multivariate control chart based on PCA mix for variable and attribute quality characteristics—0
Multivariate Density Estimation with Deep Neural Mixture Models—0
Multivariate Probabilistic Forecasting of Intraday Electricity Prices using Normalizing Flows—0
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks—0
Multi-view Generative Adversarial Networks—0
Mutual Information Continuity-constrained Estimator—0
Unsupervised Object Matching for Relational Data—0
MVMR-FS : Non-parametric feature selection algorithm based on Maximum inter-class Variation and Minimum Redundancy—0
A new effective and efficient measure for outlying aspect mining—0
NAS-Count: Counting-by-Density with Neural Architecture Search—0
TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization—0
Near-Linear Time Local Polynomial Nonparametric Estimation with Box Kernels—0
Near-minimax recursive density estimation on the binary hypercube—0
Near-Optimal Density Estimation in Near-Linear Time Using Variable-Width Histograms—0
Negative Sampling in Variational Autoencoders—0
Temporal Density Extrapolation using a Dynamic Basis Approach—0
Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data—0
Temporal Non-Volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition—0
Unsupervised Parameter-free Outlier Detection using HDBSCAN* Outlier Profiles—0
Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra—0
Neural Empirical Bayes—0
A new approach for pedestrian density estimation using moving sensors and computer vision—0
Accelerated Deep Lossless Image Coding with Unified Paralleleized GPU Coding Architecture—0
Tensor-Train Point Cloud Compression and Efficient Approximate Nearest-Neighbor Search—0
TERM Model: Tensor Ring Mixture Model for Density Estimation—0
Neural-Kernel Conditional Mean Embeddings—0
Neural-Kernelized Conditional Density Estimation—0
Testing the boundaries: Normalizing Flows for higher dimensional data sets—0
A Neural Mean Embedding Approach for Back-door and Front-door Adjustment—0
Neural Network Approach to Stochastic Dynamics for Smooth Multimodal Density Estimation—0
Neural PCA for Flow-Based Representation Learning—0
Neural Point Process for Forecasting Spatiotemporal Events—0
Neural Posterior Estimation with Differentiable Simulators—0
An Effective and Efficient Evolutionary Algorithm for Many-Objective Optimization—0
Unsupervised Skill Discovery through Skill Regions Differentiation—0
Unsupervised Video Anomaly Detection via Normalizing Flows with Implicit Latent Features—0
Optimal Coreset for Gaussian Kernel Density Estimation—0
Noise2NoiseFlow: Realistic Camera Noise Modeling without Clean Images—0
Noise Contrastive Meta-Learning for Conditional Density Estimation using Kernel Mean Embeddings—0
Using Depth for Pixel-Wise Detection of Adversarial Attacks in Crowd Counting—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