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 791–800 of 2226 papers

TitleStatusHype
A Bayesian Approach for Accurate Classification-Based Aggregates—0
Bayesian Inference with Deep Weakly Nonlinear Networks—0
A Probabilistic Framework for Dynamic Object Recognition in 3D Environment With A Novel Continuous Ground Estimation Method—0
Affine Invariant Ensemble Transform Methods to Improve Predictive Uncertainty in Neural Networks—0
Bayesian inference via rejection filtering—0
Bayesian Inference via Approximation of Log-likelihood for Priors in Exponential Family—0
A probabilistic atlas of the human thalamic nuclei combining ex vivo MRI and histology—0
Bayesian inference to improve quality of Retrieval Augmented Generation—0
A Primer on Variational Inference for Physics-Informed Deep Generative Modelling—0
A theory of representation learning gives a deep generalisation of kernel methods—0
Show:102550
← PrevPage 80 of 223Next →

Benchmark Results

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