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 601–650 of 1394 papers

TitleStatusHype
Direct estimation of density functionals using a polynomial basis—0
Dimension-independent rates for structured neural density estimation—0
Calibration Regularized Training of Deep Neural Networks using Kernel Density Estimation—0
A One-Pass Private Sketch for Most Machine Learning Tasks—0
Dihedral angle prediction using generative adversarial networks—0
Diffusion Model Based Probabilistic Day-ahead Load Forecasting—0
Calibrated and Sharp Uncertainties in Deep Learning via Density Estimation—0
A One-Class Classification Decision Tree Based on Kernel Density Estimation—0
Adaptable Embeddings Network (AEN)—0
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation—0
C^*-algebra Net: A New Approach Generalizing Neural Network Parameters to C^*-algebra—0
DiffMOD: Progressive Diffusion Point Denoising for Moving Object Detection in Remote Sensing—0
Calculating CVaR and bPOE for Common Probability Distributions With Application to Portfolio Optimization and Density Estimation—0
Differentially Private Synthetic Data with Private Density Estimation—0
Differentially Private Normalizing Flows for Privacy-Preserving Density Estimation—0
CacheFlow: Fast Human Motion Prediction by Cached Normalizing Flow—0
Answer Identification in Collaborative Organizational Group Chat—0
Differentially Private Kernel Density Estimation—0
Differentially-Private Bayes Consistency—0
ButterflyFlow: Building Invertible Layers with Butterfly Matrices—0
Deterministic Fokker-Planck Transport -- With Applications to Sampling, Variational Inference, Kernel Mean Embeddings & Sequential Monte Carlo—0
A Novel Markov Model for Near-Term Railway Delay Prediction—0
A General Approach for Determining Applicability Domain of Machine Learning Models—0
Building Detection from Satellite Images on a Global Scale—0
BSL: An R Package for Efficient Parameter Estimation for Simulation-Based Models via Bayesian Synthetic Likelihood—0
A Novel Locally Linear KNN Model for Visual Recognition—0
A Generative Adversarial Density Estimator—0
AdaFlow: Domain-Adaptive Density Estimator with Application to Anomaly Detection and Unpaired Cross-Domain Translation—0
3D-GMNet: Single-View 3D Shape Recovery as A Gaussian Mixture—0
A Statistical Relational Approach to Learning Distance-based GCNs—0
Breaking the curse of dimensionality in structured density estimation—0
A Note on Shumailov et al. (2024): `AI Models Collapse When Trained on Recursively Generated Data'—0
Designing Data: Proactive Data Collection and Iteration for Machine Learning—0
Bounds all around: training energy-based models with bidirectional bounds—0
Transporting Robotic Swarms via Mean-Field Feedback Control—0
Bounded rationality in structured density estimation—0
An optimal transport approach for selecting a representative subsample with application in efficient kernel density estimation—0
"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study—0
Bounded rationality in structured density estimation—0
Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective—0
Density estimation with LLMs: a geometric investigation of in-context learning trajectories—0
Bounded KRnet and its applications to density estimation and approximation—0
Density Estimation with Distribution Element Trees—0
Quasi-Bayesian Nonparametric Density Estimation via Autoregressive Predictive Updates—0
Density estimation via mixture discrepancy and moments—0
Density Estimation via Measure Transport: Outlook for Applications in the Biological Sciences—0
Boundary of Distribution Support Generator (BDSG): Sample Generation on the Boundary—0
A Non-Parametric Approach to Dynamic Programming—0
A General Theory for Softmax Gating Multinomial Logistic Mixture of Experts—0
Density Estimation via Discrepancy Based Adaptive Sequential Partition—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