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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 1691–1700 of 2226 papers

TitleStatusHype
Uncertainty propagation in neural networks for sparse coding—0
Bayesian Adversarial Spheres: Bayesian Inference and Adversarial Examples in a Noiseless Setting—0
Uncertainty aware audiovisual activity recognition using deep Bayesian variational inference—0
Amortized Bayesian inference for clustering modelsCode0
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
BAR: Bayesian Activity Recognition using variational inference—0
A Factor Graph Approach to Automated Design of Bayesian Signal Processing AlgorithmsCode0
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Benchmark Results

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