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 351–360 of 2226 papers

TitleStatusHype
Analytically Tractable Hidden-States Inference in Bayesian Neural Networks—0
Adaptive matching pursuit for sparse signal recovery—0
A Bayesian brain model of adaptive behavior: An application to the Wisconsin Card Sorting Task—0
Bayesian inference for dynamic spatial quantile models with interactive effects—0
Uncertainty Quantification with Statistical Guarantees in End-to-End Autonomous Driving Control—0
Adaptive Gaussian process surrogates for Bayesian inference—0
Bayesian inference as iterated random functions with applications to sequential inference in graphical models—0
Bayesian Context Aggregation for Neural Processes—0
Analysis of Langevin Monte Carlo via convex optimization—0
Bayesian Inference by Symbolic Model Checking—0
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Benchmark Results

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