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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 371–380 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
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
Efficient identification of informative features in simulation-based inference	Oct 21, 2022	Bayesian Inference	CodeCode Available	0	5
Differentially Private Bayesian Learning on Distributed Data	Mar 3, 2017	Bayesian Inference	CodeCode Available	0	5
Efficient Neural Network Approaches for Conditional Optimal Transport with Applications in Bayesian Inference	Oct 25, 2023	Bayesian InferenceComputational Efficiency	CodeCode Available	0	5
Distilling Importance Sampling for Likelihood Free Inference	Oct 8, 2019	Bayesian InferenceEpidemiology	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
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks	Dec 16, 2021	Bayesian InferenceDecision Making	CodeCode Available	0	5
Electrostatics-based particle sampling and approximate inference	Jun 28, 2024	Bayesian Inference	CodeCode Available	0	5
Amortized Variational Inference: When and Why?	Jul 20, 2023	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
Baxter Permutation Process	Dec 1, 2020	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