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 1751–1760 of 2226 papers

TitleStatusHype
A Novel Deterministic Framework for Non-probabilistic Recommender SystemsCode0
A Variational Feature Encoding Method of 3D Object for Probabilistic Semantic SLAM—0
Cortical Microcircuits from a Generative Vision Model—0
Efficient Bayesian Inference of Sigmoidal Gaussian Cox ProcessesCode0
Winner-Take-All as Basic Probabilistic Inference Unit of Neuronal Circuits—0
Towards identifying the optimal datasize for lexically-based Bayesian inference of linguistic phylogenies—0
Sprucing up the trees -- Error detection in treebanks—0
Sampling-based probabilistic inference emerges from learning in neural circuits with a cost on reliability—0
Automatic Bayesian Density Analysis—0
Efficient Probabilistic Inference in the Quest for Physics Beyond the Standard ModelCode0
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Benchmark Results

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