SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 71–80 of 2226 papers

TitleStatusHype
Bayesian neural networks via MCMC: a Python-based tutorialCode1
Bayesian Coresets: Revisiting the Nonconvex Optimization PerspectiveCode1
Bayesian inference for logistic models using Polya-Gamma latent variablesCode1
Variational multiple shooting for Bayesian ODEs with Gaussian processesCode1
Bayesian continual learning and forgetting in neural networksCode1
Bayesian differential programming for robust systems identification under uncertaintyCode1
Bayes-Newton Methods for Approximate Bayesian Inference with PSD GuaranteesCode1
Being Bayesian, Even Just a Bit, Fixes Overconfidence in ReLU NetworksCode1
A Bit More Bayesian: Domain-Invariant Learning with UncertaintyCode1
A friendly introduction to triangular transportCode1
Show:102550
← PrevPage 8 of 223Next →

Benchmark Results

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