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 1881–1890 of 2226 papers

TitleStatusHype
Bayesian Sequential Stacking Algorithm for Concurrently Designing Molecules and Synthetic Reaction Networks—0
Bayesian shrinkage in mixture of experts models: Identifying robust determinants of class membership—0
Bayesian State Estimation for Unobservable Distribution Systems via Deep Learning—0
Bayesian stochastic blockmodeling—0
Bayesian Synthesis of Probabilistic Programs for Automatic Data Modeling—0
Identification and Inference for Synthetic Control Methods with Spillover Effects: Estimating the Economic Cost of the Sudan Split—0
Bayesian System Identification based on Hierarchical Sparse Bayesian Learning and Gibbs Sampling with Application to Structural Damage Assessment—0
Bayesian taut splines for estimating the number of modes—0
Bayesian Teaching Enables Probabilistic Reasoning in Large Language Models—0
Bayes in the age of intelligent machines—0
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Benchmark Results

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