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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 1791–1800 of 2226 papers

TitleStatusHype
DLBI: Deep learning guided Bayesian inference for structure reconstruction of super-resolution fluorescence microscopyCode0
Nonparametric Bayesian Deep Networks with Local CompetitionCode0
Approximate Bayesian inference in spatial environments—0
Bayesian Joint Spike-and-Slab Graphical LassoCode0
Wasserstein Measure Coresets—0
Spatial Uncertainty Sampling for End-to-End Control—0
Improving Predictive Uncertainty Estimation using Dropout -- Hamiltonian Monte Carlo—0
Subsampling Sequential Monte Carlo for Static Bayesian Models—0
Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in BadlandsCode0
A Channel-based Exact Inference Algorithm for Bayesian Networks—0
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Benchmark Results

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