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
Swarm Intelligence Enhanced Reasoning: A Density-Driven Framework for LLM-Based Multi-Agent Optimization—0
Symmetry-Aware Marginal Density Estimation—0
Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport—0
TabADM: Unsupervised Tabular Anomaly Detection with Diffusion Models—0
TAKDE: Temporal Adaptive Kernel Density Estimator for Real-Time Dynamic Density Estimation—0
Taking a Step Back with KCal: Multi-Class Kernel-Based Calibration for Deep Neural Networks—0
TANGO: Clustering with Typicality-Aware Nonlocal Mode-Seeking and Graph-Cut Optimization—0
Temporal Logistic Neural Bag-of-Features for Financial Time series Forecasting leveraging Limit Order Book Data—0
Temporal Non-Volume Preserving Approach to Facial Age-Progression and Age-Invariant Face Recognition—0
Tensor-Train Point Cloud Compression and Efficient Approximate Nearest-Neighbor Search—0
TERM Model: Tensor Ring Mixture Model for Density Estimation—0
Testing the boundaries: Normalizing Flows for higher dimensional data sets—0
The Expxorcist: Nonparametric Graphical Models Via Conditional Exponential Densities—0
The Gaussian Process Density Sampler—0
The Gram-Charlier A Series based Extended Rule-of-Thumb for Bandwidth Selection in Univariate and Multivariate Kernel Density Estimations—0
Optimality of Maximum Likelihood for Log-Concave Density Estimation and Bounded Convex Regression—0
The Optimal Approximation Factor in Density Estimation—0
The Time-Marginalized Coalescent Prior for Hierarchical Clustering—0
Topological Feature Search Method for Multichannel EEG: Application in ADHD classification—0
Topology-Matching Normalizing Flows for Out-of-Distribution Detection in Robot Learning—0
TorchDyn: A Neural Differential Equations Library—0
Total stochastic gradient algorithms and applications in reinforcement learning—0
Toward a Characterization of Loss Functions for Distribution Learning—0
Toward Model-Agnostic Detection of New Physics Using Data-Driven Signal Regions—0
Towards Automated Animal Density Estimation with Acoustic Spatial Capture-Recapture—0
Towards Better Spherical Sliced-Wasserstein Distance Learning with Data-Adaptive Discriminative Projection Direction—0
Towards Healing the Blindness of Score Matching—0
Towards Model-Agnostic Posterior Approximation for Fast and Accurate Variational Autoencoders—0
Towards Theoretical Understandings of Self-Consuming Generative Models—0
Tracking Dynamic Gaussian Density with a Theoretically Optimal Sliding Window Approach—0
Tractable Regularization of Probabilistic Circuits—0
TraDE: A Simple Self-Attention-Based Density Estimator—0
TraDE: Transformers for Density Estimation—0
Traffic Density Estimation using a Convolutional Neural Network—0
Transfer learning for multifidelity simulation-based inference in cosmology—0
Transformation Autoregressive Networks—0
Transformer Neural Autoregressive Flows—0
Tree density estimation—0
TREND: Truncated Generalized Normal Density Estimation of Inception Embeddings for GAN Evaluation—0
Triangular Flows for Generative Modeling: Statistical Consistency, Smoothness Classes, and Fast Rates—0
Tropical Density Estimation of Phylogenetic Trees—0
Two-stage Sampled Learning Theory on Distributions—0
Ultra-High Reliability by Predictive Interference Management Using Extreme Value Theory—0
Unbiasing Enhanced Sampling on a High-dimensional Free Energy Surface with Deep Generative Model—0
Uncertainty Intervals for Graph-based Spatio-Temporal Traffic Prediction—0
Understanding Boltzmann Machine and Deep Learning via A Confident Information First Principle—0
Understanding the (un)interpretability of natural image distributions using generative models—0
UNeRF: Time and Memory Conscious U-Shaped Network for Training Neural Radiance Fields—0
Uniform Convergence Rates for Kernel Density Estimation—0
Unifying and extending Diffusion Models through PDEs for solving Inverse Problems—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