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 326350 of 1394 papers

TitleStatusHype
Bounded rationality in structured density estimation0
Bounded rationality in structured density estimation0
Latent Space Energy-based Model for Fine-grained Open Set Recognition0
Crowdotic: A Privacy-Preserving Hospital Waiting Room Crowd Density Estimation with Non-speech Audio0
Content Reduction, Surprisal and Information Density Estimation for Long Documents0
Correcting sampling biases via importance reweighting for spatial modeling0
NeuroCodeBench: a plain C neural network benchmark for software verificationCode0
Tropical Geometric Tools for Machine Learning: the TML packageCode0
Distribution learning via neural differential equations: a nonparametric statistical perspective0
Affine-Transformation-Invariant Image Classification by Differentiable Arithmetic Distribution Module0
Self-Supervision for Tackling Unsupervised Anomaly Detection: Pitfalls and Opportunities0
Arbitrary Distributions Mapping via SyMOT-Flow: A Flow-based Approach Integrating Maximum Mean Discrepancy and Optimal Transport0
Out-of-distribution detection using normalizing flows on the data manifold0
Bayesian Exploration Networks0
Towards Automated Animal Density Estimation with Acoustic Spatial Capture-Recapture0
Conditional Kernel Imitation Learning for Continuous State Environments0
Cell Spatial Analysis in Crohn's Disease: Unveiling Local Cell Arrangement Pattern with Graph-based SignaturesCode0
Fast Inference and Update of Probabilistic Density Estimation on Trajectory PredictionCode1
High-Probability Risk Bounds via Sequential Predictors0
Learning Distributions via Monte-Carlo Marginalization0
Generative Forests0
Statistical Estimation Under Distribution Shift: Wasserstein Perturbations and Minimax TheoryCode0
Adaptive learning of density ratios in RKHS0
Continual Learning in Predictive Autoscaling0
MVMR-FS : Non-parametric feature selection algorithm based on Maximum inter-class Variation and Minimum Redundancy0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1MAFLog-likelihood (nats)3,049Unverified
2DDPMNLL (bits/dim)3.69Unverified
3MRCNFNLL (bits/dim)3.54Unverified
4FFJORDNLL (bits/dim)3.4Unverified
5RNODENLL (bits/dim)3.38Unverified
6Pixel CNNNLL (bits/dim)3.03Unverified
7score SDENLL (bits/dim)2.99Unverified
8Flow matchingNLL (bits/dim)2.99Unverified
9Pixel CNN ++NLL (bits/dim)2.92Unverified
10Image TransformerNLL (bits/dim)2.9Unverified
#ModelMetricClaimedVerifiedStatus
1DVP-VAENLL77.1Unverified
2PaddingFlowMMD-L211Unverified
3FFJORDNLL (bits/dim)0.99Unverified
4RNODENLL (bits/dim)0.97Unverified
5IdentityNLL (bits/dim)0.13Unverified
6MADE MoGLog-likelihood (nats)-1,038.5Unverified
#ModelMetricClaimedVerifiedStatus
1nMDMALog-likelihood1.78Unverified
2DDELog-likelihood0.97Unverified
3B-NAFLog-likelihood0.61Unverified
4FFJORDLog-likelihood0.46Unverified
5MADE MoGLog-likelihood0.4Unverified
6PaddingFlowCD0.14Unverified
#ModelMetricClaimedVerifiedStatus
1TANLog-likelihood159.8Unverified
2FFJORDLog-likelihood157.4Unverified
3B-NAFLog-likelihood157.36Unverified
4MADE MoGLog-likelihood153.71Unverified
5PaddingFlowCD0.5Unverified
#ModelMetricClaimedVerifiedStatus
1GlowNLL (bits/dim)4.09Unverified
2Image TransformerNLL (bits/dim)3.77Unverified
3VDMNLL (bits/dim)3.72Unverified
4i-DODENLL (bits/dim)3.69Unverified
5MuLANNLL (bits/dim)3.67Unverified
#ModelMetricClaimedVerifiedStatus
1B-NAFLog-likelihood12.06Unverified
2DDELog-likelihood9.73Unverified
3FFJORDLog-likelihood8.59Unverified
4MADE MoGLog-likelihood8.47Unverified
5PaddingFlowCD0.89Unverified
#ModelMetricClaimedVerifiedStatus
1PaddingFlowCD13.8Unverified
2DDELog-likelihood-11.3Unverified
3B-NAFLog-likelihood-14.71Unverified
4FFJORDLog-likelihood-14.92Unverified
5MADE MoGLog-likelihood-15.15Unverified
#ModelMetricClaimedVerifiedStatus
1PaddingFlowCD24.5Unverified
2DDELog-likelihood-6.94Unverified
3B-NAFLog-likelihood-8.95Unverified
4FFJORDLog-likelihood-10.43Unverified
5MADE MoGLog-likelihood-12.27Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO98.33Unverified
2B-NAFNegative ELBO94.83Unverified
3DVp-VAENLL89.07Unverified
4PaddingFlowMMD-L220.3Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO104.03Unverified
2B-NAFNegative ELBO94.91Unverified
3PaddingFlowMMD-L217.9Unverified
#ModelMetricClaimedVerifiedStatus
1FFJORDNegative ELBO4.39Unverified
2B-NAFNegative ELBO4.33Unverified
3PaddingFlowMMD-L20.62Unverified
#ModelMetricClaimedVerifiedStatus
1RNODELog-likelihood1.04Unverified
#ModelMetricClaimedVerifiedStatus
1MAFLog-likelihood5,872Unverified
#ModelMetricClaimedVerifiedStatus
1RNODELog-likelihood3.83Unverified