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 1561–1570 of 2226 papers

TitleStatusHype
Inference of epidemiological parameters from household stratified data—0
Inferential Moments of Uncertain Multivariable Systems—0
Inferring Atmospheric Properties of Exoplanets with Flow Matching and Neural Importance Sampling—0
Inferring ground truth from multi-annotator ordinal data: a probabilistic approach—0
Inferring perceptual decision making parameters from behavior in production and reproduction tasks—0
Inferring to C or not to C: Evolutionary games with Bayesian inferential strategies—0
Classifying Turbulent Environments via Machine Learning—0
Infinite Ends from Finite Samples: Open-Ended Goal Inference as Top-Down Bayesian Filtering of Bottom-Up Proposals—0
Infinite Latent SVM for Classification and Multi-task Learning—0
InfoNCE is variational inference in a recognition parameterised model—0
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Benchmark Results

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