SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1421–1430 of 2226 papers

TitleStatusHype
Variational Bayes: A report on approaches and applications—0
Variational Bayes Decomposition for Inverse Estimation with Superimposed Multispectral Intensity—0
Variational Bayes Deep Operator Network: A data-driven Bayesian solver for parametric differential equations—0
Variational Bayes for Merging Noisy Databases—0
Variational Bayesian Inference Clustering Based Joint User Activity and Data Detection for Grant-Free Random Access in mMTC—0
Variational Bayesian Inference for Crowdsourcing Predictions—0
Variational Bayesian Inference For A Scale Mixture Of Normal Distributions Handling Missing Data—0
Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers—0
Variational Bayesian inference for CP tensor completion with side information—0
Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified