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 251–300 of 1394 papers

TitleStatusHype
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
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
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
Median of Forests for Robust Density Estimation—0
Kernel-Based Anomaly Detection Using Generalized Hyperbolic ProcessesCode0
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
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
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
Non-Normal Diffusion Models—0
Score Change of Variables—0
VQ4ALL: Efficient Neural Network Representation via a Universal Codebook—0
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
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
Summarizing Bayesian Nonparametric Mixture Posterior -- Sliced Optimal Transport Metrics for Gaussian MixturesCode0
Dimension-independent rates for structured neural density estimation—0
Adaptable Embeddings Network (AEN)—0
Eliminating Ratio Bias for Gradient-based Simulated Parameter Estimation—0
Unsupervised Parameter-free Outlier Detection using HDBSCAN* Outlier Profiles—0
Expected Information Gain Estimation via Density Approximations: Sample Allocation and Dimension Reduction—0
Your copula is a classifier in disguise: classification-based copula density estimationCode0
You are out of context!—0
XNB: Explainable Class-Specific NaIve-Bayes ClassifierCode0
Conformalized High-Density Quantile Regression via Dynamic Prototypes-based Probability Density EstimationCode0
Minibatch Optimal Transport and Perplexity Bound Estimation in Discrete Flow Matching—0
Statistical-Computational Trade-offs for Density Estimation—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
7Flow matchingNLL (bits/dim)2.99—Unverified
8score SDENLL (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