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 861–870 of 2226 papers

TitleStatusHype
Black-box Coreset Variational InferenceCode0
Fully Bayesian inference for latent variable Gaussian process modelsCode0
Ensemble transport smoothing. Part I: Unified frameworkCode0
Ensemble transport smoothing. Part II: Nonlinear updatesCode0
Federated Averaging Langevin Dynamics: Toward a unified theory and new algorithms—0
SoftBart: Soft Bayesian Additive Regression Trees—0
Bayesian Inference of Transition Matrices from Incomplete Graph Data with a Topological Prior—0
Bayesian Methods in Automated Vehicle's Car-following Uncertainties: Enabling Strategic Decision Making—0
Variational Bayesian Inference Clustering Based Joint User Activity and Data Detection for Grant-Free Random Access in mMTC—0
GFlowOut: Dropout with Generative Flow Networks—0
Show:102550
← PrevPage 87 of 223Next →

Benchmark Results

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