SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1371–1380 of 2226 papers

TitleStatusHype
Estimating the impact of non-pharmaceutical interventions and vaccination on the progress of the COVID-19 epidemic in Mexico: a mathematical approach—0
Estimation of the incubation period and generation time of SARS-CoV-2 Alpha and Delta variants from contact tracing data—0
Evaluating Scalable Uncertainty Estimation Methods for DNN-Based Molecular Property Prediction—0
Evaluation of Machine Learning Techniques for Green Energy Prediction—0
Event-horizon-scale Imaging of M87* under Different Assumptions via Deep Generative Image Priors—0
Event Temporal Relation Extraction with Bayesian Translational Model—0
Evidence of Replica Symmetry Breaking under the Nishimori conditions in epidemic inference on graphs—0
Evolutionary MCMC Sampling and Optimization in Discrete Spaces—0
Exact Bayesian inference for off-line change-point detection in tree-structured graphical models—0
Excess risk analysis for epistemic uncertainty with application to variational inference—0
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Benchmark Results

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