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 1731–1740 of 2226 papers

TitleStatusHype
An easy-to-use empirical likelihood ABC method—0
Sketching for Latent Dirichlet-Categorical Models—0
Uncertainty-aware generative models for inferring document class prevalenceCode0
Bayesian Prediction of Future Street Scenes using Synthetic LikelihoodsCode0
Variational Bayesian Inference for Audio-Visual Tracking of Multiple Speakers—0
Adaptive Gaussian process surrogates for Bayesian inference—0
Bayesian inference for PCA and MUSIC algorithms with unknown number of sourcesCode0
Practical bounds on the error of Bayesian posterior approximations: A nonasymptotic approach—0
Flexible Mixture Modeling on Constrained Spaces—0
Simulator Calibration under Covariate Shift with Kernels—0
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Benchmark Results

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