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 2171–2180 of 2226 papers

TitleStatusHype
Extended molt phenology models improve inferences about molt duration and timingCode0
Testing and Improving the Robustness of Amortized Bayesian Inference for Cognitive ModelsCode0
Bayesian Inference ForgettingCode0
Unbiased Bayesian Inference for Population Markov Jump Processes via Random TruncationsCode0
Variational Inference for Graph Convolutional Networks in the Absence of Graph Data and Adversarial SettingsCode0
Variational Inference in Location-Scale Families: Exact Recovery of the Mean and Correlation MatrixCode0
Bayesian PseudocoresetsCode0
Bayesian Inference for Consistent Predictions in Overparameterized Nonlinear RegressionCode0
InVAErt networks for amortized inference and identifiability analysis of lumped parameter hemodynamic modelsCode0
Invariant polynomials and machine learningCode0
Show:102550
← PrevPage 218 of 223Next →

Benchmark Results

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