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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 681–690 of 2226 papers

Title	Date	Tasks	Status	Hype
QCM-SGM+: Improved Quantized Compressed Sensing With Score-Based Generative Models	Feb 2, 2023	Bayesian Inferencecompressed sensing	CodeCode Available	1
Kernel Stein Discrepancy thinning: a theoretical perspective of pathologies and a practical fix with regularization	Jan 31, 2023	Bayesian Inference	CodeCode Available	0
Adaptive sparseness for correntropy-based robust regression via automatic relevance determination	Jan 31, 2023	Bayesian Inferencefeature selection	—Unverified	0
Classified as unknown: A novel Bayesian neural network	Jan 31, 2023	Bayesian InferenceBinary Classification	—Unverified	0
Differentially Private Distributed Bayesian Linear Regression with MCMC	Jan 31, 2023	Bayesian InferencePrivacy Preserving	CodeCode Available	0
Optimally-Weighted Estimators of the Maximum Mean Discrepancy for Likelihood-Free Inference	Jan 27, 2023	Bayesian Inferenceparameter estimation	CodeCode Available	0
Coin Sampling: Gradient-Based Bayesian Inference without Learning Rates	Jan 26, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0
Neural Continuous-Discrete State Space Models for Irregularly-Sampled Time Series	Jan 26, 2023	Bayesian InferenceImputation	CodeCode Available	1
Projective Integral Updates for High-Dimensional Variational Inference	Jan 20, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0
Robust Gaussian Process Regression with Huber Likelihood	Jan 19, 2023	Bayesian Inferenceregression	—Unverified	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