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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 131–140 of 2226 papers

Title	Date	Tasks	Status	Hype
BayesDLL: Bayesian Deep Learning Library	Sep 22, 2023	Bayesian InferenceDeep Learning	CodeCode Available	1
A Simple Baseline for Bayesian Uncertainty in Deep Learning	Feb 7, 2019	Bayesian InferenceDeep Learning	CodeCode Available	1
A Probabilistic State Space Model for Joint Inference from Differential Equations and Data	Mar 18, 2021	Bayesian Inference	CodeCode Available	1
Automatic Posterior Transformation for Likelihood-Free Inference	May 17, 2019	Bayesian InferenceTime Series	CodeCode Available	1
A Bayesian approach for extracting free energy profiles from cryo-electron microscopy experiments using a path collective variable	Feb 3, 2021	3D ReconstructionBayesian Inference	CodeCode Available	1
Bayesian Adversarial Human Motion Synthesis	Jun 1, 2020	Bayesian InferenceData Augmentation	CodeCode Available	1
Bayesian Coresets: Revisiting the Nonconvex Optimization Perspective	Jul 1, 2020	Bayesian Inference	CodeCode Available	1
Bayesian differential programming for robust systems identification under uncertainty	Apr 15, 2020	Bayesian InferenceModel Discovery	CodeCode Available	1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric Approaches	Apr 15, 2020	Bayesian InferenceCausal Inference	CodeCode Available	1
Antipodes of Label Differential Privacy: PATE and ALIBI	Jun 7, 2021	Bayesian InferenceMemorization	CodeCode Available	1

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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