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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 2081–2090 of 2226 papers

Title	Date	Tasks	Status	Hype
Online, Informative MCMC Thinning with Kernelized Stein Discrepancy	Jan 18, 2022	Bayesian Inference	CodeCode Available	0
Online neural connectivity estimation with ensemble stimulation	Jul 27, 2020	Bayesian Inferencecompressed sensing	CodeCode Available	0
A Scalable Laplace Approximation for Neural Networks	Jan 1, 2018	Bayesian Inference	CodeCode Available	0
Heterogeneous Multi-Task Gaussian Cox Processes	Aug 29, 2023	Bayesian InferenceData Augmentation	CodeCode Available	0
On Markov chain Monte Carlo methods for tall data	May 11, 2015	Bayesian Inference	CodeCode Available	0
Adaptive Nonparametric Perturbations of Parametric Bayesian Models	Dec 14, 2024	Bayesian InferenceCausal Inference	CodeCode Available	0
Accelerated Stein Variational Gradient Flow	Mar 30, 2025	Bayesian Inference	CodeCode Available	0
Hierarchical Bayesian inference for community detection and connectivity of functional brain networks	Jan 18, 2023	Bayesian InferenceCommunity Detection	CodeCode Available	0
Are Bayesian neural networks intrinsically good at out-of-distribution detection?	Jul 26, 2021	Bayesian InferenceOut-of-Distribution Detection	CodeCode Available	0
On Sequential Bayesian Inference for Continual Learning	Jan 4, 2023	Bayesian InferenceContinual Learning	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