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 651–700 of 1394 papers

TitleStatusHype
Out-of-distribution detection using normalizing flows on the data manifold—0
Overcoming Catastrophic Forgetting with Gaussian Mixture Replay—0
High-Dimensional Non-Parametric Density Estimation in Mixed Smooth Sobolev Spaces—0
Parallel Multiscale Autoregressive Density Estimation—0
Parameter and density estimation from real-world traffic data: A kinetic compartmental approach—0
Parametric Copula-GP model for analyzing multidimensional neuronal and behavioral relationships—0
Parametric Density Estimation with Uncertainty using Deep Ensembles—0
Particle approximations of the score and observed information matrix for parameter estimation in state space models with linear computational cost—0
PDE-Inspired Algorithms for Semi-Supervised Learning on Point Clouds—0
PEDENet: Image Anomaly Localization via Patch Embedding and Density Estimation—0
Performance analysis for L\_2 kernel classification—0
Permutation invariant functions: statistical tests, density estimation, and computationally efficient embedding—0
Persistent Homology for Learning Densities with Bounded Support—0
PGNAA Spectral Classification of Metal with Density Estimations—0
Plots of the cumulative differences between observed and expected values of ordered Bernoulli variates—0
Plug-and-play dual-tree algorithm runtime analysis—0
Point Cloud Generation with Continuous Conditioning—0
Point Localization and Density Estimation from Ordinal kNN graphs using Synchronization—0
Crime Hot-Spot Modeling via Topic Modeling and Relative Density Estimation—0
Predicting Ambulance Demand: Challenges and Methods—0
Predicting the probability distribution of bus travel time to move towards reliable planning of public transport services—0
Prediction of Vessel Arrival Time to Pilotage Area Using Multi-Data Fusion and Deep Learning—0
Preference learning made easy: Everything should be understood through win rate—0
Pre-trained Language Models as Re-Annotators—0
Principal Component Density Estimation for Scenario Generation Using Normalizing Flows—0
Principal Manifold Flows—0
Prior Flow Variational Autoencoder: A density estimation model for Non-Intrusive Load Monitoring—0
Prior Learning in Introspective VAEs—0
Private Edge Density Estimation for Random Graphs: Optimal, Efficient and Robust—0
Private Statistical Estimation of Many Quantiles—0
Probabilistic Dipole Inversion for Adaptive Quantitative Susceptibility Mapping—0
Probabilistic Forecast-based Portfolio Optimization of Electricity Demand at Low Aggregation Levels—0
Probabilistic Low-Rank Subspace Clustering—0
Probabilistic Net Load Forecasting for High-Penetration RES Grids Utilizing Enhanced Conditional Diffusion Model—0
Probabilistic reachable sets of stochastic nonlinear systems with contextual uncertainties—0
Probabilistic Segmentation via Total Variation Regularization—0
Probabilistic Time Series Forecasting of Residential Loads -- A Copula Approach—0
Probability Density Estimation Based Imitation Learning—0
Process monitoring based on orthogonal locality preserving projection with maximum likelihood estimation—0
Product Manifold Filter: Non-Rigid Shape Correspondence via Kernel Density Estimation in the Product Space—0
Progressive Bayesian Particle Flows based on Optimal Transport Map Sequences—0
Projection pursuit based on Gaussian mixtures and evolutionary algorithms—0
Proper-Composite Loss Functions in Arbitrary Dimensions—0
PSD Representations for Effective Probability Models—0
Pythae: Unifying Generative Autoencoders in Python -- A Benchmarking Use Case—0
The Hidden Uncertainty in a Neural Networks Activations—0
Quantum Deep Sets and Sequences—0
Quantum Measurement Classification with Qudits—0
Quasi-Bayes meets Vines—0
Quickest Change Detection with Leave-one-out 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