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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 1121–1130 of 2226 papers

TitleStatusHype
Priors in Bayesian Deep Learning: A Review—0
High-Performance FPGA-based Accelerator for Bayesian Neural Networks—0
A new framework for experimental design using Bayesian Evidential Learning: the case of wellhead protection areaCode1
Multiscale Invertible Generative Networks for High-Dimensional Bayesian Inference—0
Bayesian inference and superstatistics to describe long memory processes of financial time series—0
Deep Neural Networks as Point Estimates for Deep Gaussian Processes—0
A Bit More Bayesian: Domain-Invariant Learning with UncertaintyCode1
Laplace Matching for fast Approximate Inference in Latent Gaussian ModelsCode0
MCMC-driven importance samplers—0
Bayesian Logistic Shape Model Inference: application to cochlea image segmentation—0
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Benchmark Results

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