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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 671–680 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
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
Simulation-based Bayesian Inference from Privacy Protected Data	Oct 19, 2023	Bayesian InferenceTime Series	CodeCode Available	0	5
Conditional diffusions for amortized neural posterior estimation	Oct 24, 2024	Bayesian InferenceBenchmarking	CodeCode Available	0	5
Conditionally Independent Multiresolution Gaussian Processes	Feb 25, 2018	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
Conditional Optimal Transport on Function Spaces	Nov 9, 2023	Bayesian Inference	CodeCode Available	0	5
Deep surrogate accelerated delayed-acceptance HMC for Bayesian inference of spatio-temporal heat fluxes in rotating disc systems	Apr 5, 2022	Bayesian Inference	CodeCode Available	0	5
Discovering Inductive Bias with Gibbs Priors: A Diagnostic Tool for Approximate Bayesian Inference	Mar 7, 2022	Bayesian InferenceDiagnostic	CodeCode Available	0	5
Bayesian Online Prediction of Change Points	Feb 12, 2019	Bayesian InferenceChange Point Detection	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

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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