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 411–420 of 2226 papers

TitleStatusHype
Bayesian Inference for Gaussian Process Classifiers with Annealing and Pseudo-Marginal MCMC—0
A Novel Resource Allocation for Anti-jamming in Cognitive-UAVs: an Active Inference Approach—0
Bayesian Inference for Jump-Diffusion Approximations of Biochemical Reaction Networks—0
Bayesian Inference for Large Scale Image Classification—0
Analysing Quality of English-Hindi Machine Translation Engine Outputs Using Bayesian Classification—0
A category theory framework for Bayesian learning—0
Bayesian Inference of Transition Matrices from Incomplete Graph Data with a Topological Prior—0
Bayesian inference for low rank spatiotemporal neural receptive fields—0
Bayesian Inference for Multidimensional Welfare Comparisons—0
Bayesian inference on random simple graphs with power law degree distributions—0
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Benchmark Results

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