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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 1971–1980 of 2226 papers

TitleStatusHype
Efficient Attack Graph Analysis through Approximate Inference—0
Bayesian Inference on Matrix Manifolds for Linear Dimensionality Reduction—0
A unified approach to mortality modelling using state-space framework: characterisation, identification, estimation and forecasting—0
Merging MCMC Subposteriors through Gaussian-Process Approximations—0
PAC-Bayesian Theory Meets Bayesian Inference—0
Variational Bayesian Inference for Hidden Markov Models With Multivariate Gaussian Output Distributions—0
Communication-Efficient Distributed Statistical Inference—0
Coresets for Scalable Bayesian Logistic RegressionCode0
ABC random forests for Bayesian parameter inference—0
An Efficient and Flexible Spike Train Model via Empirical Bayes—0
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Benchmark Results

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