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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 1711–1720 of 2226 papers

TitleStatusHype
Surrogate-assisted parallel tempering for Bayesian neural learningCode0
Bayesian Inference for Structural Vector Autoregressions Identified by Markov-Switching HeteroskedasticityCode0
Black-Box Autoregressive Density Estimation for State-Space Models—0
Informed MCMC with Bayesian Neural Networks for Facial Image Analysis—0
A Factor Graph Approach to Automated Design of Bayesian Signal Processing AlgorithmsCode0
BAR: Bayesian Activity Recognition using variational inference—0
Bayesian State Estimation for Unobservable Distribution Systems via Deep Learning—0
Learning and Inference in Hilbert Space with Quantum Graphical Models—0
Towards Principled Uncertainty Estimation for Deep Neural Networks—0
Mean-field theory of graph neural networks in graph partitioning—0
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Benchmark Results

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