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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 2131–2140 of 2226 papers

TitleStatusHype
Exploring Action-Centric Representations Through the Lens of Rate-Distortion Theory—0
Expressive yet Tractable Bayesian Deep Learning via Subnetwork Inference—0
Extending the statistical software package Engine for Likelihood-Free Inference—0
Extension of compressive sampling to binary vector recovery for model-based defect imaging—0
Factorized Asymptotic Bayesian Inference for Factorial Hidden Markov Models—0
Factorized Asymptotic Bayesian Inference for Latent Feature Models—0
False Discovery Rate Control via Frequentist-assisted Horseshoe—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
Fast Approximate Inference of Transcript Expression Levels from RNA-seq Data—0
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Benchmark Results

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