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 1711–1720 of 2226 papers

TitleStatusHype
Metropolis-Hastings view on variational inference and adversarial training—0
Bayesian Inference of Self-intention Attributed by Observer—0
Variational Bayesian Monte CarloCode1
Uncertainty in Neural Networks: Approximately Bayesian EnsemblingCode0
Dropout as a Structured Shrinkage PriorCode0
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
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Benchmark Results

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