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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
Network Plasticity as Bayesian InferenceCode0
A closed-form approach to Bayesian inference in tree-structured graphical models—0
Bidirectional Recurrent Neural Networks as Generative Models - Reconstructing Gaps in Time Series—0
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
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Benchmark Results

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