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 51–100 of 1394 papers

TitleStatusHype
Nonparametric spectral density estimation using interactive mechanisms under local differential privacy—0
KEVS: Enhancing Segmentation of Visceral Adipose Tissue in Pre-Cystectomy CT with Gaussian Kernel Density Estimation—0
Squared families: Searching beyond regular probability models—0
A friendly introduction to triangular transportCode1
Debiasing Kernel-Based Generative Models—0
A New Stochastic Approximation Method for Gradient-based Simulated Parameter Estimation—0
Food Recommendation With Balancing Comfort and Curiosity—0
Neural Network Approach to Stochastic Dynamics for Smooth Multimodal Density Estimation—0
Probabilistic Net Load Forecasting for High-Penetration RES Grids Utilizing Enhanced Conditional Diffusion Model—0
Explainable Graph-theoretical Machine Learning: with Application to Alzheimer's Disease Prediction—0
Enhanced ECG Arrhythmia Detection Accuracy by Optimizing Divergence-Based Data Fusion—0
Nonlinear Bayesian Update via Ensemble Kernel Regression with Clustering and Subsampling—0
Hierarchical clustering with maximum density paths and mixture modelsCode0
Counterfactual experience augmented off-policy reinforcement learningCode0
Decentralized Continuification Control of Multi-Agent Systems via Distributed Density Estimation—0
Flows on convex polytopesCode0
On the contraction properties of Sinkhorn semigroups—0
Scaling Probabilistic Circuits via Data PartitioningCode0
Dynamic DBSCAN with Euler Tour Sequences—0
Learning Energy-Based Models by Self-normalising the Likelihood—0
Diffusion Model Based Probabilistic Day-ahead Load Forecasting—0
Exploring the usage of Probabilistic Neural Networks for Ionospheric electron density estimation—0
RANGE: Retrieval Augmented Neural Fields for Multi-Resolution Geo-Embeddings—0
Mixture models for data with unknown distributions—0
A Fokker-Planck-Based Loss Function that Bridges Dynamics with Density Estimation—0
Flow-based Bayesian filtering for high-dimensional nonlinear stochastic dynamical systems—0
Mixup Regularization: A Probabilistic Perspective—0
Flow-based generative models as iterative algorithms in probability space—0
Efficient Learning Under Density Shift in Incremental Settings Using Cramér-Rao-Based Regularization—0
Continual Learning Should Move Beyond Incremental Classification—0
Preference learning made easy: Everything should be understood through win rate—0
Causal Covariate Shift Correction using Fisher information penalty—0
Generative Modeling with Bayesian Sample InferenceCode1
Distribution learning via neural differential equations: minimal energy regularization and approximation theory—0
Convolution-Based Converter : A Weak-Prior Approach For Modeling Stochastic Processes Based On Conditional Density Estimation—0
Decoding-based RegressionCode3
Enhancing Synthetic Oversampling for Imbalanced Datasets Using Proxima-Orion Neighbors and q-Gaussian Weighting Technique—0
Estimating the Optimal Number of Clusters in Categorical Data Clustering by Silhouette Coefficient—0
Kernel-Based Anomaly Detection Using Generalized Hyperbolic ProcessesCode0
Median of Forests for Robust Density Estimation—0
TrajFlow: A Generative Framework for Occupancy Density Estimation Using Normalizing FlowsCode0
Ultra-High Reliability by Predictive Interference Management Using Extreme Value Theory—0
Robust Local Polynomial Regression with Similarity KernelsCode0
Robust density estimation over star-shaped density classes—0
Distributed Nonparametric Estimation: from Sparse to Dense Samples per Terminal—0
Likelihood Training of Cascaded Diffusion Models via Hierarchical Volume-preserving MapsCode0
Stochastic Process Learning via Operator Flow MatchingCode1
Cosmological Parameter Estimation with Sequential Linear Simulation-based InferenceCode0
NeuroPMD: Neural Fields for Density Estimation on Product ManifoldsCode0
Nonparametric estimation of a factorizable density using diffusion models—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