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Bayesian Inference

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

Papers

Recently Added Most Hyped Most Active Needs Verification Most Verified

Showing 1901–1910 of 2226 papers

Title	Date	Tasks	Status	Hype
Calibration and Filtering of Exponential L\'evy Option Pricing Models	May 13, 2017	Bayesian Inferenceparameter estimation	—Unverified	0
Forecasting using incomplete models	May 12, 2017	Bayesian Inference	—Unverified	0
Bayesian Image Quality Transfer with CNNs: Exploring Uncertainty in dMRI Super-Resolution	May 1, 2017	Bayesian InferenceImage Generation	—Unverified	0
Sharing deep generative representation for perceived image reconstruction from human brain activity	Apr 25, 2017	Bayesian InferenceImage Reconstruction	CodeCode Available	0
Mixture modeling on related samples by ψ-stick breaking and kernel perturbation	Apr 17, 2017	Bayesian Inference	—Unverified	0
Metropolis Sampling	Apr 15, 2017	Bayesian Inference	—Unverified	0
Stochastic Gradient Descent as Approximate Bayesian Inference	Apr 13, 2017	Bayesian Inference	CodeCode Available	0
Object proposal generation applying the distance dependent Chinese restaurant process	Apr 12, 2017	Bayesian InferenceObject	CodeCode Available	0
Bayesian Inference of Individualized Treatment Effects using Multi-task Gaussian Processes	Apr 10, 2017	Bayesian Inferencecounterfactual	CodeCode Available	0
Stein Variational Policy Gradient	Apr 7, 2017	Bayesian Inferencecontinuous-control	—Unverified	0

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Benchmark Results

#	Model	Metric	Claimed	Verified	Status
1	F-SWA	Accuracy	83.61	—	Unverified
2	F-SWAG	Accuracy	80.93	—	Unverified