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 1421–1430 of 2226 papers

TitleStatusHype
Model Uncertainty Quantification for Reliable Deep Vision Structural Health Monitoring—0
Active recursive Bayesian inference using Rényi information measures—0
B-SCST: Bayesian Self-Critical Sequence Training for Image Captioning—0
The equivalence between Stein variational gradient descent and black-box variational inference—0
Regression Approach for Modeling COVID-19 Spread and its Impact On Stock Market—0
Bayesian ODE Solvers: The Maximum A Posteriori Estimate—0
A Bayesian brain model of adaptive behavior: An application to the Wisconsin Card Sorting Task—0
Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of componentsCode0
An Empirical Evaluation on Robustness and Uncertainty of Regularization Methods—0
The Variational InfoMax Learning Objective—0
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Benchmark Results

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