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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 651–700 of 1394 papers

TitleStatusHype
Neural Flows: Efficient Alternative to Neural ODEsCode1
Adaptive Fusion Affinity Graph with Noise-free Online Low-rank Representation for Natural Image SegmentationCode0
PixelPyramids: Exact Inference Models from Lossless Image PyramidsCode1
Diffusion Normalizing FlowCode1
A neural simulation-based inference approach for characterizing the Galactic Center γ-ray excessCode0
Information Theoretic Structured Generative ModelingCode0
Knothe-Rosenblatt transport for Unsupervised Domain Adaptation—0
Implicit Riemannian Concave Potential Maps—0
ARMCMC: Online Bayesian Density Estimation of Model Parameters—0
Mutual Information Continuity-constrained Estimator—0
Discovering the neural correlate informed nosological relation among multiple neuropsychiatric disorders through dual utilisation of diagnostic information—0
Kernel Density Decision Trees—0
Calibration Regularized Training of Deep Neural Networks using Kernel Density Estimation—0
Density Estimation for Conservative Q-Learning—0
FlowVocoder: A small Footprint Neural Vocoder based Normalizing flow for Speech Synthesis—0
Fast Density Estimation for Density-based Clustering Methods—0
Towards Zero and Few-shot Knowledge-seeking Turn Detection in Task-orientated Dialogue SystemsCode0
Exploring the Training Robustness of Distributional Reinforcement Learning against Noisy State ObservationsCode0
Types of Out-of-Distribution Texts and How to Detect ThemCode1
On the use of Wasserstein metric in topological clustering of distributional data—0
Stationary Density Estimation of Itô Diffusions Using Deep Learning—0
Sharp regret bounds for empirical Bayes and compound decision problems—0
Computing on Functions Using Randomized Vector Representations—0
Semiparametric Bayesian NetworksCode1
Estimation of Bivariate Structural Causal Models by Variational Gaussian Process Regression Under Likelihoods Parametrised by Normalising Flows—0
Deep Dive into Semi-Supervised ELBO for Improving Classification Performance—0
Efficient training of lightweight neural networks using Online Self-Acquired Knowledge Distillation—0
Benchmarking high-fidelity pedestrian tracking systems for research, real-time monitoring and crowd control—0
A survey on Bayesian inference for Gaussian mixture model—0
Moser Flow: Divergence-based Generative Modeling on ManifoldsCode1
Neural density estimation and uncertainty quantification for laser induced breakdown spectroscopy spectra—0
Hierarchical Infinite Relational ModelCode1
First Order Locally Orderless Registration—0
Continuous Language Generative FlowCode1
Tensor-Train Density EstimationCode1
Kernel Density Estimation by Stagewise Algorithm with a Simple Dictionary—0
Data-driven deep density estimationCode0
Boundary of Distribution Support Generator (BDSG): Sample Generation on the Boundary—0
ByPE-VAE: Bayesian Pseudocoresets Exemplar VAECode0
Quantum Measurement Classification with Qudits—0
Constrained Sampling from a Kernel Density Estimator to Generate Scenarios for the Assessment of Automated Vehicles—0
MD-split+: Practical Local Conformal Inference in High Dimensions—0
DEANN: Speeding up Kernel-Density Estimation using Approximate Nearest Neighbor SearchCode1
On Out-of-distribution Detection with Energy-based ModelsCode1
Short-term probabilistic photovoltaic power forecast based on deep convolutional long short-term memory network and kernel density estimation—0
Variational Diffusion ModelsCode1
PSD Representations for Effective Probability Models—0
Identifying High Accuracy Regions in Traffic Camera Images to Enhance the Estimation of Road Traffic Metrics: A Quadtree-Based Method—0
ADAVI: Automatic Dual Amortized Variational Inference Applied To Pyramidal Bayesian Models—0
Stratified Learning: A General-Purpose Statistical Method for Improved Learning under Covariate Shift—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