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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 751–800 of 1394 papers

TitleStatusHype
Score-Debiased Kernel Density Estimation—0
Segmentation of patchy areas in biomedical images based on local edge density estimation—0
Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities—0
Semantic Place Descriptors for Classification and Map Discovery—0
Semi-supervised Learning with Missing Values Imputation—0
Semi-Supervised Learning for Bone Mineral Density Estimation in Hip X-ray Images—0
SENIOR: Efficient Query Selection and Preference-Guided Exploration in Preference-based Reinforcement Learning—0
Sensitivity-Aware Density Estimation in Multiple Dimensions—0
Sensory Integration and Density Estimation—0
Sequential Density Estimation via Nonlinear Continuous Weighted Finite Automata—0
Sequential prediction under log-loss and misspecification—0
Sharp regret bounds for empirical Bayes and compound decision problems—0
Short-term probabilistic photovoltaic power forecast based on deep convolutional long short-term memory network and kernel density estimation—0
Simultaneous Learning of Trees and Representations for Extreme Classification and Density Estimation—0
SKYNET: an efficient and robust neural network training tool for machine learning in astronomy—0
Sliced Multi-Marginal Optimal Transport—0
SMURF: Spatial Multi-Representation Fusion for 3D Object Detection with 4D Imaging Radar—0
Some techniques in density estimation—0
Space evaluation at the starting point of soccer transitions—0
Sparse Density Estimation with Measurement Errors—0
End-to-End Multi-Object Detection with a Regularized Mixture Model—0
Improving Discrete Latent Representations With Differentiable Approximation Bridges—0
Spatial probabilistic pulsatility model for enhancing photoplethysmographic imaging systems—0
COVID-19 mortality analysis from soft-data multivariate curve regression and machine learning—0
SpecAE: Spectral AutoEncoder for Anomaly Detection in Attributed Networks—0
Specialization in Hierarchical Learning Systems—0
Spectral-Spatial Diffusion Geometry for Hyperspectral Image Clustering—0
Spectral Toolkit of Algorithms for Graphs: Technical Report (2)—0
SPINEX: Similarity-based Predictions with Explainable Neighbors Exploration for Anomaly and Outlier Detection—0
Squared families: Searching beyond regular probability models—0
Stationary Density Estimation of Itô Diffusions Using Deep Learning—0
Statistical-Computational Trade-offs for Density Estimation—0
Statistical Guarantees for Transformation Based Models with Applications to Implicit Variational Inference—0
Statistical Modeling of Univariate Multimodal Data—0
Statistical Pattern Recognition for Driving Styles Based on Bayesian Probability and Kernel Density Estimation—0
Statistical Perspective of Top-K Sparse Softmax Gating Mixture of Experts—0
Statistical post-processing of wind speed forecasts using convolutional neural networks—0
Stochastic force inference via density estimation—0
Stochastic geometry to generalize the Mondrian Process—0
Stratified Learning: A General-Purpose Statistical Method for Improved Learning under Covariate Shift—0
Strong posterior contraction rates via Wasserstein dynamics—0
Strong Uniform Consistency with Rates for Kernel Density Estimators with General Kernels on Manifolds—0
Structured Neural Networks for Density Estimation and Causal Inference—0
Sub-linear Memory Sketches for Near Neighbor Search on Streaming Data with RACE—0
Sub-linear RACE Sketches for Approximate Kernel Density Estimation on Streaming Data—0
Submanifold density estimation—0
Sub-quadratic Algorithms for Kernel Matrices via Kernel Density Estimation—0
Summable Reparameterizations of Wasserstein Critics in the One-Dimensional Setting—0
Supervised Anomaly Detection based on Deep Autoregressive Density Estimators—0
Surprisal Driven k-NN for Robust and Interpretable Nonparametric Learning—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