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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 721–730 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Deep Bayesian Structure Networks	Sep 25, 2019	Bayesian InferenceNeural Architecture Search	CodeCode Available	0	5
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	CodeCode Available	0	5
A Scalable Laplace Approximation for Neural Networks	Jan 1, 2018	Bayesian Inference	CodeCode Available	0	5
Physics-Informed Sylvester Normalizing Flows for Bayesian Inference in Magnetic Resonance Spectroscopy	May 6, 2025	Bayesian InferenceDecoder	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
Bayesian Neural Controlled Differential Equations for Treatment Effect Estimation	Oct 26, 2023	Bayesian InferenceDecision Making	CodeCode Available	0	5
Bayesian multiscale deep generative model for the solution of high-dimensional inverse problems	Feb 4, 2021	Bayesian Inferenceparameter estimation	CodeCode Available	0	5
Practical calibration of the temperature parameter in Gibbs posteriors	Apr 22, 2020	Bayesian Inference	CodeCode Available	0	5
Stein Point Markov Chain Monte Carlo	May 9, 2019	Bayesian Inference	CodeCode Available	0	5
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal 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