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 1011–1020 of 2226 papers

TitleStatusHype
Pathologies in priors and inference for Bayesian transformers—0
Kernel Interpolation as a Bayes Point MachineCode0
De-randomizing MCMC dynamics with the diffusion Stein operator—0
MetaCOG: A Hierarchical Probabilistic Model for Learning Meta-Cognitive Visual RepresentationsCode0
Procedure Planning in Instructional Videos via Contextual Modeling and Model-based Policy Learning—0
Kalman Bayesian Neural Networks for Closed-form Online Learning—0
Semantic Classification and Learning Using a Linear Tranformation Model in a Probabilistic Type Theory with Records—0
Arbitrary Marginal Neural Ratio Estimation for Simulation-based InferenceCode0
EinSteinVI: General and Integrated Stein Variational Inference—0
On the Implicit Biases of Architecture & Gradient Descent—0
Show:102550
← PrevPage 102 of 223Next →

Benchmark Results

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