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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 561–570 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Bayesian task embedding for few-shot Bayesian optimization	Jan 2, 2020	Bayesian InferenceBayesian Optimization	CodeCode Available	0	5
Detecting structural perturbations from time series with deep learning	Jun 9, 2020	Bayesian InferenceDeep Learning	CodeCode Available	0	5
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	CodeCode Available	0	5
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
Differentially Private Distributed Bayesian Linear Regression with MCMC	Jan 31, 2023	Bayesian InferencePrivacy Preserving	CodeCode Available	0	5
Bayeslands: A Bayesian inference approach for parameter uncertainty quantification in Badlands	May 2, 2018	Bayesian InferenceUncertainty Quantification	CodeCode Available	0	5
Deep Neural Networks as Gaussian Processes	Nov 1, 2017	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
Bayesian score calibration for approximate models	Nov 10, 2022	Bayesian Inferencescoring rule	CodeCode Available	0	5
A Compact Representation for Bayesian Neural Networks By Removing Permutation Symmetry	Dec 31, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0	5
Bayesian Robust Aggregation for Federated Learning	May 5, 2025	Bayesian InferenceFederated 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