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 801–850 of 1394 papers

TitleStatusHype
Learning Unsupervised Word Mapping by Maximizing Mean Discrepancy—0
A Note on Shumailov et al. (2024): `AI Models Collapse When Trained on Recursively Generated Data'—0
Learn to Scale: Generating Multipolar Normalized Density Maps for Crowd Counting—0
LED: Latent Variable-based Estimation of Density—0
A-CCNN: adaptive ccnn for density estimation and crowd counting—0
Leveraging Heterogeneous Auxiliary Tasks to Assist Crowd Counting—0
LieDetect: Detection of representation orbits of compact Lie groups from point clouds—0
Lie PCA: Density estimation for symmetric manifolds—0
An optimal transport approach for selecting a representative subsample with application in efficient kernel density estimation—0
Likelihood-Free Adaptive Bayesian Inference via Nonparametric Distribution Matching—0
Likelihood-free inference of experimental Neutrino Oscillations using Neural Spline Flows—0
Stratified Learning: A General-Purpose Statistical Method for Improved Learning under Covariate Shift—0
Linear-time Algorithms for Pairwise Statistical Problems—0
Liouville PDE-based sliced-Wasserstein flow for fair regression—0
LMD3: Language Model Data Density Dependence—0
A Non-Parametric Approach to Dynamic Programming—0
Strong posterior contraction rates via Wasserstein dynamics—0
Localised Generative Flows—0
Strong Uniform Consistency with Rates for Kernel Density Estimators with General Kernels on Manifolds—0
A Non-Classical Parameterization for Density Estimation Using Sample Moments—0
Structured Neural Networks for Density Estimation and Causal Inference—0
Unsupervised in-distribution anomaly detection of new physics through conditional density estimation—0
LoMar: A Local Defense Against Poisoning Attack on Federated Learning—0
Lossless Compression using Continuously-Indexed Normalizing Flows—0
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data with RACE—0
Lumbar Bone Mineral Density Estimation from Chest X-ray Images: Anatomy-aware Attentive Multi-ROI Modeling—0
Lyapunov Density Models: Constraining Distribution Shift in Learning-Based Control—0
Machine and Deep Learning for Crowd Analytics—0
Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data—0
Anomaly Subsequence Detection with Dynamic Local Density for Time Series—0
Anomaly Detection of Time Series with Smoothness-Inducing Sequential Variational Auto-Encoder—0
MAE: Mutual Posterior-Divergence Regularization for Variational AutoEncoders—0
MammoFL: Mammographic Breast Density Estimation using Federated Learning—0
Manifold Density Estimation via Generalized Dequantization—0
Manifold Density Estimation via Generalized Dequantization—0
Manifold Learning Using Kernel Density Estimation and Local Principal Components Analysis—0
Manifold Optimization for Gaussian Mixture Models—0
Mapping oil palm density at country scale: An active learning approach—0
Anomaly Detection in Trajectory Data with Normalizing Flows—0
Markov Balance Satisfaction Improves Performance in Strictly Batch Offline Imitation Learning—0
Anomaly Detection Based on Unsupervised Disentangled Representation Learning in Combination with Manifold Learning—0
Masked Language Modeling Becomes Conditional Density Estimation for Tabular Data Synthesis—0
AnoDODE: Anomaly Detection with Diffusion ODE—0
Matrix Manifold Optimization for Gaussian Mixtures—0
Maximum a Posteriori on a Submanifold: a General Image Restoration Method with GAN—0
Tuning Parameter-Free Nonparametric Density Estimation from Tabulated Summary Data—0
Maximum Entropy Model Correction in Reinforcement Learning—0
Maximum Multiscale Entropy and Neural Network Regularization—0
MCD: Marginal Contrastive Discrimination for conditional density estimation—0
MCNet: A crowd denstity estimation network based on integrating multiscale attention module—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