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 711–720 of 2226 papers

TitleStatusHype
Amortized Variational Inference: When and Why?Code0
A Bayesian Programming Approach to Car-following Model Calibration and Validation using Limited Data—0
Bayesian inference for data-efficient, explainable, and safe robotic motion planning: A review—0
Flexible and efficient emulation of spatial extremes processes via variational autoencodersCode0
FedBIAD: Communication-Efficient and Accuracy-Guaranteed Federated Learning with Bayesian Inference-Based Adaptive Dropout—0
Variational Prediction—0
Bayesian taut splines for estimating the number of modes—0
A generative flow for conditional sampling via optimal transportCode0
Incentive-Theoretic Bayesian Inference for Collaborative Science—0
Uncertainty Informed Optimal Resource Allocation with Gaussian Process based Bayesian Inference—0
Show:102550
← PrevPage 72 of 223Next →

Benchmark Results

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