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 701–710 of 2226 papers

TitleStatusHype
Bistable perception, precision and neuromodulationCode0
Bayesian posterior approximation with stochastic ensemblesCode0
Bayesian data fusion with shared priors—0
Traffic Flow Prediction via Variational Bayesian Inference-based Encoder-Decoder Framework—0
A compartmental model for Xylella fastidiosa diseases with explicit vector seasonal dynamics—0
Further analysis of multilevel Stein variational gradient descent with an application to the Bayesian inference of glacier ice models—0
PRISM: Probabilistic Real-Time Inference in Spatial World Models—0
Multielement polynomial chaos Kriging-based metamodelling for Bayesian inference of non-smooth systems—0
Are you using test log-likelihood correctly?—0
Trust and Time Preference: Measuring a Causal Effect in a Random-Assignment Experiment—0
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Benchmark Results

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