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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 341–350 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Bayesian Approaches to Shrinkage and Sparse Estimation	Dec 22, 2021	Bayesian Inferencequantile regression	CodeCode Available	0	5
PDE-constrained Gaussian process surrogate modeling with uncertain data locations	May 19, 2023	Bayesian Inferenceregression	CodeCode Available	0	5
Bayesian at heart: Towards autonomic outflow estimation via generative state-space modelling of heart rate dynamics	Mar 8, 2023	Bayesian InferenceDecision Making	CodeCode Available	0	5
Bayesian posterior repartitioning for nested sampling	Aug 13, 2019	Bayesian InferenceUnity	CodeCode Available	0	5
Learning to infer in recurrent biological networks	Jun 18, 2020	Bayesian InferenceVariational Inference	CodeCode Available	0	5
Deep Learning and genetic algorithms for cosmological Bayesian inference speed-up	May 6, 2024	Bayesian InferenceHyperparameter Optimization	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
Demonstrating the Continual Learning Capabilities and Practical Application of Discrete-Time Active Inference	Sep 30, 2024	Bayesian InferenceContinual Learning	CodeCode Available	0	5
Dependent Multinomial Models Made Easy: Stick Breaking with the Pólya-Gamma Augmentation	Jun 18, 2015	Bayesian InferencePosition	CodeCode Available	0	5
deBInfer: Bayesian inference for dynamical models of biological systems in R	Oct 15, 2016	Bayesian Inference	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