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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 221–230 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
A General Framework for Uncertainty Estimation in Deep Learning	Jul 16, 2019	Autonomous DrivingBayesian Inference	CodeCode Available	0	5
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling	Dec 1, 2019	Bayesian InferenceDeblurring	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
A Bayesian Perspective on the Deep Image Prior	Apr 16, 2019	Bayesian InferenceDenoising	CodeCode Available	0	5
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	CodeCode Available	0	5
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal 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
A fast asynchronous MCMC sampler for sparse Bayesian inference	Aug 14, 2021	Bayesian Inference	CodeCode Available	0	5
A Bayesian Monte Carlo approach for predicting the spread of infectious diseases	Apr 26, 2019	Bayesian InferenceDisease Prediction	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