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 101–150 of 1394 papers

TitleStatusHype
Shift the Lens: Environment-Aware Unsupervised Camouflaged Object DetectionCode0
DiSciPLE: Learning Interpretable Programs for Scientific Visual Discovery—0
Adversarial Attack and Defense for LoRa Device Identification and Authentication via Deep Learning—0
Diverse Rare Sample Generation with Pretrained GANsCode0
Towards Better Spherical Sliced-Wasserstein Distance Learning with Data-Adaptive Discriminative Projection Direction—0
Hypergraph Attacks via Injecting Homogeneous Nodes into Elite Hyperedges—0
Statistical Modeling of Univariate Multimodal Data—0
A Unifying Information-theoretic Perspective on Evaluating Generative Models—0
A partial likelihood approach to tree-based density modeling and its application in Bayesian inference—0
Volumetric Mapping with Panoptic Refinement via Kernel Density Estimation for Mobile RobotsCode1
Non-Normal Diffusion Models—0
Score Change of Variables—0
VQ4ALL: Efficient Neural Network Representation via a Universal Codebook—0
Normalizing Flows are Capable Generative ModelsCode3
MIMO Detection under Hardware Impairments: Data Augmentation With Boosting—0
Tabular data generation with tensor contraction layers and transformersCode0
Vision Transformers for Weakly-Supervised Microorganism EnumerationCode0
Hierarchical VAE with a Diffusion-based VampPriorCode0
Uncovering Process Noise in LTV Systems via Kernel DeconvolutionCode0
Revisiting Generative Policies: A Simpler Reinforcement Learning Algorithmic PerspectiveCode2
Spatiotemporal Density Correction of Multivariate Global Climate Model Projections using Deep Learning—0
Implicit High-Order Moment Tensor Estimation and Learning Latent Variable Models—0
Dimension-independent rates for structured neural density estimation—0
Summarizing Bayesian Nonparametric Mixture Posterior -- Sliced Optimal Transport Metrics for Gaussian MixturesCode0
Adaptable Embeddings Network (AEN)—0
Eliminating Ratio Bias for Gradient-based Simulated Parameter Estimation—0
Expected Information Gain Estimation via Density Approximations: Sample Allocation and Dimension Reduction—0
Unsupervised Parameter-free Outlier Detection using HDBSCAN* Outlier Profiles—0
Your copula is a classifier in disguise: classification-based copula density estimationCode0
You are out of context!—0
Conformalized High-Density Quantile Regression via Dynamic Prototypes-based Probability Density EstimationCode0
XNB: Explainable Class-Specific NaIve-Bayes ClassifierCode0
Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching—0
Video prediction using score-based conditional density estimation—0
Statistical-Computational Trade-offs for Density Estimation—0
Non-intrusive Speech Quality Assessment with Diffusion Models Trained on Clean Speech—0
Governing equation discovery of a complex system from snapshots—0
MIK: Modified Isolation Kernel for Biological Sequence Visualization, Classification, and Clustering—0
WeSpeR: Population spectrum retrieval and spectral density estimation of weighted sample covariance—0
A Note on Shumailov et al. (2024): `AI Models Collapse When Trained on Recursively Generated Data'—0
Generalized Distribution Prediction for Asset ReturnsCode0
TSDS: Data Selection for Task-Specific Model FinetuningCode1
Conditional Density Estimation with Histogram TreesCode0
Deterministic Fokker-Planck Transport -- With Applications to Sampling, Variational Inference, Kernel Mean Embeddings & Sequential Monte Carlo—0
Breaking the curse of dimensionality in structured density estimation—0
Continuous Contrastive Learning for Long-Tailed Semi-Supervised RecognitionCode1
Density estimation with LLMs: a geometric investigation of in-context learning trajectories—0
Tensor-Train Point Cloud Compression and Efficient Approximate Nearest-Neighbor Search—0
Inference with K-means—0
Local Flow Matching Generative ModelsCode0
Show:102550
← PrevPage 3 of 28Next →
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