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 931–940 of 2226 papers

TitleStatusHype
Bayesian Inference with Nonlinear Generative Models: Comments on Secure Learning—0
Bayesian inference of spatial and temporal relations in AI patents for EU countries—0
Asymptotic properties of Bayesian inference in linear regression with a structural break—0
Online, Informative MCMC Thinning with Kernelized Stein DiscrepancyCode0
Incorporating Bayesian approaches in Deep Learning Research—0
A visual exploration of Gaussian Processes and Infinite Neural Networks—0
Bayesian sense of time in biological and artificial brains—0
An Overview of Uncertainty Quantification Methods for Infinite Neural Networks—0
Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture ModelsCode0
Fully Adaptive Bayesian Algorithm for Data Analysis, FABADACode1
Show:102550
← PrevPage 94 of 223Next →

Benchmark Results

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