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 551–600 of 1394 papers

TitleStatusHype
Flow-based Bayesian filtering for high-dimensional nonlinear stochastic dynamical systems—0
Continuous LWE is as Hard as LWE & Applications to Learning Gaussian Mixtures—0
A multi-reconstruction study of breast density estimation using Deep Learning—0
Flexible conditional density estimation for time series—0
Attentional Neural Fields for Crowd Counting—0
Highly Efficient Self-Adaptive Reward Shaping for Reinforcement Learning—0
Gradient density estimation in arbitrary finite dimensions using the method of stationary phase—0
Grenander-type Density Estimation under Myerson Regularity—0
Hierarchical correlation reconstruction with missing data, for example for biology-inspired neuron—0
First Order Locally Orderless Registration—0
Continuous Assortment Optimization with Logit Choice Probabilities under Incomplete Information—0
Attend To Count: Crowd Counting with Adaptive Capacity Multi-scale CNNs—0
Field Estimation using Robotic Swarms through Bayesian Regression and Mean-Field Feedback—0
Continual Learning with Fully Probabilistic Models—0
Few-shot Autoregressive Density Estimation: Towards Learning to Learn Distributions—0
Feedback Interconnected Mean-Field Density Estimation and Control—0
Continual Learning Should Move Beyond Incremental Classification—0
A Multi-model Combination Approach for Probabilistic Wind Power Forecasting—0
Estimating Pore Location of PBF-LB/M Processes with Segmentation Models—0
Federated Learning for distribution skewed data using sample weights—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
FedBoost: A Communication-Efficient Algorithm for Federated Learning—0
FIS-GAN: GAN with Flow-based Importance Sampling—0
Continual Learning in Predictive Autoscaling—0
Continuous Graph Flow—0
Feature Selection For High-Dimensional Clustering—0
Flow-based generative models as iterative algorithms in probability space—0
Contextual Hourglass Networks for Segmentation and Density Estimation—0
Flow-based Self-supervised Density Estimation for Anomalous Sound Detection—0
Feature Density Estimation for Out-of-Distribution Detection via Normalizing Flows—0
Feature-aware Adaptation and Density Alignment for Crowd Counting in Video Surveillance—0
Amortized Inference Regularization—0
Fast rates in statistical and online learning—0
A System of ODEs for Representing Trends of CGM Signals—0
Contraction of Locally Differentially Private Mechanisms—0
Geometric Estimation of Multivariate Dependency—0
FlowVocoder: A small Footprint Neural Vocoder based Normalizing flow for Speech Synthesis—0
Decomposing Global Bank Network Connectedness: What is Common, Idiosyncratic and When?—0
Goal-Oriented Bayesian Optimal Experimental Design for Nonlinear Models using Markov Chain Monte Carlo—0
Fast optimization of Multithreshold Entropy Linear Classifier—0
Fast On-Line Kernel Density Estimation for Active Object Localization—0
From Identifiable Causal Representations to Controllable Counterfactual Generation: A Survey on Causal Generative Modeling—0
From optimal score matching to optimal sampling—0
Content-aware Density Map for Crowd Counting and Density Estimation—0
Frustratingly Easy Model Ensemble for Abstractive Summarization—0
Fully-Connected CRFs with Non-Parametric Pairwise Potential—0
Convergence rates of a partition based Bayesian multivariate density estimation method—0
Constrained Sampling from a Kernel Density Estimator to Generate Scenarios for the Assessment of Automated Vehicles—0
Fast Multi-Class Probabilistic Classifier by Sparse Non-parametric Density Estimation—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
7score SDENLL (bits/dim)2.99—Unverified
8Flow matchingNLL (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