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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 31–40 of 2226 papers

TitleStatusHype
Bayesian hierarchical stacking: Some models are (somewhere) usefulCode1
BayesianFitForecast: A User-Friendly R Toolbox for Parameter Estimation and Forecasting with Ordinary Differential EquationsCode1
Bayesian Diffusion Models for 3D Shape ReconstructionCode1
Bayesian inference for logistic models using Polya-Gamma latent variablesCode1
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU NetworksCode1
Bayesian Adversarial Human Motion SynthesisCode1
BayesFlow: Learning complex stochastic models with invertible neural networksCode1
Bayesian continual learning and forgetting in neural networksCode1
BayesDLL: Bayesian Deep Learning LibraryCode1
A Bit More Bayesian: Domain-Invariant Learning with UncertaintyCode1
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Benchmark Results

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