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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 731–740 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	CodeCode Available	0	5
Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure	Nov 22, 2019	Bayesian InferenceNeural Architecture Search	CodeCode Available	0	5
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal Inference	CodeCode Available	0	5
deBInfer: Bayesian inference for dynamical models of biological systems in R	Oct 15, 2016	Bayesian Inference	CodeCode Available	0	5
Deep Bayesian Structure Networks	Sep 25, 2019	Bayesian InferenceNeural Architecture Search	CodeCode Available	0	5
Deep Neural Networks as Gaussian Processes	Nov 1, 2017	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
Differentially Private Federated Variational Inference	Nov 24, 2019	Bayesian InferenceFederated Learning	CodeCode Available	0	5
Dynamical Hyperspectral Unmixing with Variational Recurrent Neural Networks	Mar 19, 2023	Bayesian InferenceHyperspectral Unmixing	CodeCode Available	0	5
Fast Bayesian Inference for Neutrino Non-Standard Interactions at Dark Matter Direct Detection Experiments	May 23, 2024	Bayesian InferenceGPU	CodeCode Available	0	5
Pairwise Comparisons with Flexible Time-Dynamics	Mar 18, 2019	Bayesian InferenceGaussian Processes	CodeCode Available	0	5

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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