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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 951–960 of 2226 papers

TitleStatusHype
False Discovery Rate Control via Frequentist-assisted Horseshoe—0
Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks—0
Forget-SVGD: Particle-Based Bayesian Federated Unlearning—0
Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence—0
Fast and Flexible Bayesian Inference in Time-varying Parameter Regression Models—0
Fast and Order-invariant Inference in Bayesian VARs with Non-Parametric Shocks—0
A Tractable Fully Bayesian Method for the Stochastic Block Model—0
Bayesian Inference with Deep Weakly Nonlinear Networks—0
Bayesian inference with finitely wide neural networks—0
A time-varying finance-led model for U.S. business cycles—0
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Benchmark Results

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