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 1961–1970 of 2226 papers

TitleStatusHype
Compressed sensing reconstruction using Expectation Propagation—0
Computing the quality of the Laplace approximation—0
Concentration of the matrix-valued minimum mean-square error in optimal Bayesian inference—0
Conditional score-based diffusion models for solving inverse problems in mechanics—0
Conditional simulation via entropic optimal transport: Toward non-parametric estimation of conditional Brenier maps—0
Confidence Calibration for Convolutional Neural Networks Using Structured Dropout—0
Confidence Estimation via Sequential Likelihood Mixing—0
Confidence in Large Language Model Evaluation: A Bayesian Approach to Limited-Sample Challenges—0
Confident in the Crowd: Bayesian Inference to Improve Data Labelling in Crowdsourcing—0
Conjugate Natural Selection—0
Show:102550
← PrevPage 197 of 223Next →

Benchmark Results

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