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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 2091–2100 of 2226 papers

Title	Date	Tasks	Status	Hype
AGEM: Solving Linear Inverse Problems via Deep Priors and Sampling	Dec 1, 2019	Bayesian InferenceDeblurring	CodeCode Available	0
A fast asynchronous MCMC sampler for sparse Bayesian inference	Aug 14, 2021	Bayesian Inference	CodeCode Available	0
Hierarchical Semi-Implicit Variational Inference with Application to Diffusion Model Acceleration	Oct 26, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0
On the Convergence of the Shapley Value in Parametric Bayesian Learning Games	May 16, 2022	Bayesian Inference	CodeCode Available	0
Scalable Metropolis-Hastings for Exact Bayesian Inference with Large Datasets	Jan 28, 2019	Bayesian Inference	CodeCode Available	0
Scalable Modeling of Spatiotemporal Data using the Variational Autoencoder: an Application in Glaucoma	Aug 24, 2019	Bayesian Inference	CodeCode Available	0
Subspace Inference for Bayesian Deep Learning	Jul 17, 2019	Bayesian InferenceDeep Learning	CodeCode Available	0
Kernel Interpolation as a Bayes Point Machine	Oct 8, 2021	Bayesian Inference	CodeCode Available	0
HINT: Hierarchical Invertible Neural Transport for Density Estimation and Bayesian Inference	May 25, 2019	Bayesian InferenceDensity Estimation	CodeCode Available	0
Scalable Nonparametric Sampling from Multimodal Posteriors with the Posterior Bootstrap	Feb 8, 2019	Bayesian Inferenceregression	CodeCode Available	0

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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