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 211–220 of 2226 papers

TitleStatusHype
Bayesian Approaches for Revealing Complex Neural Network Dynamics in Parkinson's Disease—0
ELBOing Stein: Variational Bayes with Stein Mixture InferenceCode0
KALAM: toolKit for Automating high-Level synthesis of Analog computing systeMs—0
Full-waveform earthquake source inversion using simulation-based inferenceCode0
Variational Bayes Decomposition for Inverse Estimation with Superimposed Multispectral Intensity—0
BSD: a Bayesian framework for parametric models of neural spectraCode2
A Stein Gradient Descent Approach for Doubly Intractable Distributions—0
Embedded Nonlocal Operator Regression (ENOR): Quantifying model error in learning nonlocal operators—0
Dimension reduction via score ratio matching—0
TRADE: Transfer of Distributions between External Conditions with Normalizing FlowsCode0
Show:102550
← PrevPage 22 of 223Next →

Benchmark Results

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