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 1051–1060 of 2226 papers

TitleStatusHype
Bayesian sense of time in biological and artificial brains—0
A Survey of Uncertainty Estimation in LLMs: Theory Meets Practice—0
A Latent Space Theory for Emergent Abilities in Large Language Models—0
Goal-Directed Planning by Reinforcement Learning and Active Inference—0
Global Approximate Inference via Local Linearisation for Temporal Gaussian Processes—0
A stochastic version of Stein Variational Gradient Descent for efficient sampling—0
Global seismic monitoring as probabilistic inference—0
Bayesian Reinforcement Learning: A Survey—0
A Kolmogorov-Smirnov test for the molecular clock on Bayesian ensembles of phylogenies—0
A Kernel Learning Method for Backward SDE Filter—0
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Benchmark Results

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