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 2091–2100 of 2226 papers

TitleStatusHype
Efficient Weight-Space Laplace-Gaussian Filtering and Smoothing for Sequential Deep Learning—0
EinSteinVI: General and Integrated Stein Variational Inference—0
Elements of Sequential Monte Carlo—0
Eliciting Language Model Behaviors with Investigator Agents—0
Embarrassingly parallel MCMC using deep invertible transformations—0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
EMG Pattern Recognition via Bayesian Inference with Scale Mixture-Based Stochastic Generative Models—0
EMHMM Simulation Study—0
Enhanced gradient-based MCMC in discrete spaces—0
Enhancing Graphical Lasso: A Robust Scheme for Non-Stationary Mean Data—0
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Benchmark Results

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