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 531–540 of 2226 papers

TitleStatusHype
Semi-Implicit Variational Inference via Score MatchingCode0
On Estimating the Gradient of the Expected Information Gain in Bayesian Experimental DesignCode0
Accelerated Bayesian imaging by relaxed proximal-point Langevin samplingCode0
Bayesian polynomial neural networks and polynomial neural ordinary differential equations—0
Adaptive mitigation of time-varying quantum noise—0
Monte Carlo guided Diffusion for Bayesian linear inverse problemsCode1
Natural Evolution Strategies as a Black Box Estimator for Stochastic Variational Inference—0
Bayesian Flow NetworksCode2
Gradient-Based Markov Chain Monte Carlo for MIMO Detection—0
A Review of Change of Variable Formulas for Generative Modeling—0
Show:102550
← PrevPage 54 of 223Next →

Benchmark Results

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