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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 2061–2070 of 2226 papers

TitleStatusHype
A Parzen-based distance between probability measures as an alternative of summary statistics in Approximate Bayesian Computation—0
Sparse Bayesian Dictionary Learning with a Gaussian Hierarchical Model—0
Hamiltonian ABC—0
Scalable Variational Inference in Log-supermodular Models—0
Montblanc: GPU accelerated Radio Interferometer Measurement Equations in support of Bayesian Inference for Radio Observations—0
Fast Approximate Inference of Transcript Expression Levels from RNA-seq Data—0
Unbiased Bayes for Big Data: Paths of Partial Posteriors—0
Marginal likelihood and model selection for Gaussian latent tree and forest models—0
Expectation propagation as a way of life: A framework for Bayesian inference on partitioned dataCode0
Decoupled Variational Gaussian Inference—0
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Benchmark Results

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