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 961–970 of 2226 papers

TitleStatusHype
Fast Bayesian Inference for Gaussian Cox Processes via Path Integral Formulation—0
Fast Bayesian Inference for Non-Conjugate Gaussian Process Regression—0
A time-varying finance-led model for U.S. business cycles—0
Flexible Bayesian Inference on Partially Observed Epidemics—0
Fast Convergence for Langevin Diffusion with Manifold Structure—0
Fast Convergence for Langevin with Matrix Manifold Structure—0
A theory of data variability in Neural Network Bayesian inference—0
Fast Dual Variational Inference for Non-Conjugate LGMs—0
Sampling from Log-Concave Distributions over Polytopes via a Soft-Threshold Dikin Walk—0
BayesPy: Variational Bayesian Inference in Python—0
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Benchmark Results

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