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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 261–270 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
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
Data-driven Approach for Interpolation of Sparse Data	May 2, 2025	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
AdvancedHMC.jl: A robust, modular and efficient implementation of advanced HMC algorithms	Oct 16, 2019	Bayesian InferenceBenchmarking	CodeCode Available	0	5
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	CodeCode Available	0	5
deBInfer: Bayesian inference for dynamical models of biological systems in R	Oct 15, 2016	Bayesian Inference	CodeCode Available	0	5
Approximate Bayesian Inference for a Mechanistic Model of Vesicle Release at a Ribbon Synapse	Dec 1, 2019	Bayesian InferenceDescriptive	CodeCode Available	0	5
CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data	Dec 3, 2015	Bayesian InferenceCommon Sense Reasoning	CodeCode Available	0	5
A Bayesian Method for Joint Clustering of Vectorial Data and Network Data	Oct 24, 2017	Bayesian InferenceClustering	CodeCode Available	0	5
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	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