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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 311–320 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Deep Bayesian Structure Networks	Sep 25, 2019	Bayesian InferenceNeural Architecture Search	CodeCode Available	0	5
Projective Integral Updates for High-Dimensional Variational Inference	Jan 20, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0	5
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation	Nov 21, 2023	Bayesian Inference	CodeCode Available	0	5
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal Inference	CodeCode Available	0	5
Adaptive Nonparametric Perturbations of Parametric Bayesian Models	Dec 14, 2024	Bayesian InferenceCausal Inference	CodeCode Available	0	5
deBInfer: Bayesian inference for dynamical models of biological systems in R	Oct 15, 2016	Bayesian Inference	CodeCode Available	0	5
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	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
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net	Sep 25, 2017	Bayesian Inferenceregression	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