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 1891–1900 of 2226 papers

TitleStatusHype
BayesLDM: A Domain-Specific Language for Probabilistic Modeling of Longitudinal Data—0
BayesPy: Variational Bayesian Inference in Python—0
Belief functions induced by random fuzzy sets: A general framework for representing uncertain and fuzzy evidence—0
Belief patterns with information processing—0
Beta Residuals: Improving Fault-Tolerant Control for Sensory Faults via Bayesian Inference and Precision Learning—0
Beyond Prior Limits: Addressing Distribution Misalignment in Particle Filtering—0
Bézier Curve Gaussian Processes—0
Biases and Variability from Costly Bayesian Inference—0
Bias or Optimality? Disentangling Bayesian Inference and Learning Biases in Human Decision-Making—0
BIBI: Bayesian Inference of Breed Composition—0
Show:102550
← PrevPage 190 of 223Next →

Benchmark Results

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