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 421–430 of 2226 papers

TitleStatusHype
Bayesian Inference for NMR Spectroscopy with Applications to Chemical Quantification—0
Bayesian Inference for Optimal Transport with Stochastic Cost—0
A Parameter-Free Learning Automaton Scheme—0
Data Augementation with Polya Inverse Gamma—0
Bayesian Inference for Radar Imagery Based Surveillance—0
Bayesian inference for spatio-temporal spike-and-slab priors—0
A Parzen-based distance between probability measures as an alternative of summary statistics in Approximate Bayesian Computation—0
Bayesian Inference for Structured Spike and Slab Priors—0
Bayesian inference for the mixed conditional heteroskedasticity model—0
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning—0
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Benchmark Results

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