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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 1161–1170 of 2226 papers

TitleStatusHype
Approximate Bayesian inference and forecasting in huge-dimensional multi-country VARs—0
Modeling tail risks of inflation using unobserved component quantile regressionsCode1
Nishimori meets Bethe: a spectral method for node classification in sparse weighted graphsCode0
Gaussian processes meet NeuralODEs: A Bayesian framework for learning the dynamics of partially observed systems from scarce and noisy dataCode1
A Hamiltonian Monte Carlo Model for Imputation and Augmentation of Healthcare DataCode0
Parsimonious Inference—0
A practical tutorial on Variational BayesCode1
Multifidelity Ensemble Kalman Filtering Using Surrogate Models Defined by Physics-Informed Autoencoders—0
Stein Variational Gradient Descent: many-particle and long-time asymptotics—0
Sparse online variational Bayesian regressionCode0
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Benchmark Results

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