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

Showing 401–450 of 1394 papers

TitleStatusHype
Quasi-Bayesian Nonparametric Density Estimation via Autoregressive Predictive Updates—0
Density Estimation with Distribution Element Trees—0
Density estimation with LLMs: a geometric investigation of in-context learning trajectories—0
Density Forecasts in Panel Data Models: A Semiparametric Bayesian Perspective—0
Efficiently Computing Similarities to Private Datasets—0
"Dependency Bottleneck" in Auto-encoding Architectures: an Empirical Study—0
Crowd Transformer Network—0
Crowdotic: A Privacy-Preserving Hospital Waiting Room Crowd Density Estimation with Non-speech Audio—0
Designing Data: Proactive Data Collection and Iteration for Machine Learning—0
Bounds all around: training energy-based models with bidirectional bounds—0
Breaking the curse of dimensionality in structured density estimation—0
Autoregressive Score Matching—0
A Statistical Relational Approach to Learning Distance-based GCNs—0
Expected Information Gain Estimation via Density Approximations: Sample Allocation and Dimension Reduction—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
CrowdDiff: Multi-hypothesis Crowd Density Estimation using Diffusion Models—0
A General Approach for Determining Applicability Domain of Machine Learning Models—0
Crowd Density Estimation using Novel Feature Descriptor—0
Autoregressive Quantile Flows for Predictive Uncertainty Estimation—0
Differentially-Private Bayes Consistency—0
Differentially Private Kernel Density Estimation—0
Adversarial Attack and Defense for LoRa Device Identification and Authentication via Deep Learning—0
Answer Identification in Collaborative Organizational Group Chat—0
CacheFlow: Fast Human Motion Prediction by Cached Normalizing Flow—0
Differentially Private Synthetic Data with Private Density Estimation—0
DiffMOD: Progressive Diffusion Point Denoising for Moving Object Detection in Remote Sensing—0
Crowd Density Estimation using Imperfect Labels—0
C^*-algebra Net: A New Approach Generalizing Neural Network Parameters to C^*-algebra—0
Diffusion-Model-Assisted Supervised Learning of Generative Models for Density Estimation—0
A Neural Mean Embedding Approach for Back-door and Front-door Adjustment—0
A Comparative study of Artificial Neural Networks Using Reinforcement learning and Multidimensional Bayesian Classification Using Parzen Density Estimation for Identification of GC-EIMS Spectra of Partially Methylated Alditol Acetates—0
Crowd Counting and Density Estimation by Trellis Encoder-Decoder Networks—0
Dihedral angle prediction using generative adversarial networks—0
Dimension-independent rates for structured neural density estimation—0
Calibration Regularized Training of Deep Neural Networks using Kernel Density Estimation—0
Direct estimation of density functionals using a polynomial basis—0
Direct Importance Estimation with Model Selection and Its Application to Covariate Shift Adaptation—0
Crowd Counting and Density Estimation by Trellis Encoder-Decoder Network—0
DiSciPLE: Learning Interpretable Programs for Scientific Visual Discovery—0
Discovering the neural correlate informed nosological relation among multiple neuropsychiatric disorders through dual utilisation of diagnostic information—0
Discovery and density estimation of latent confounders in Bayesian networks with evidence lower bound—0
Discrepancy, Coresets, and Sketches in Machine Learning—0
Case Studies for Computing Density of Reachable States for Safe Autonomous Motion Planning—0
Cauchy-Schwarz Regularized Autoencoder—0
Automating Inference of Binary Microlensing Events with Neural Density Estimation—0
Distances for WiFi Based Topological Indoor Mapping—0
Distances with mixed type variables some modified Gower's coefficients—0
Distilling Normalizing Flows—0
Anomaly Detection for Non-stationary Time Series using Recurrent Wavelet Probabilistic Neural Network—0
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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