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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 2141–2150 of 2226 papers

Title	Date	Tasks	Status	Hype
Parameterizing pressure-temperature profiles of exoplanet atmospheres with neural networks	Sep 6, 2023	Bayesian Inference	CodeCode Available	0
In-Context Learning through the Bayesian Prism	Jun 8, 2023	Bayesian InferenceIn-Context Learning	CodeCode Available	0
Adaptive Gaussian process approximation for Bayesian inference with expensive likelihood functions	Mar 29, 2017	Active LearningBayesian Inference	CodeCode Available	0
Semi-Implicit Variational Inference	May 28, 2018	Bayesian InferenceVariational Inference	CodeCode Available	0
Semi-Implicit Variational Inference via Score Matching	Aug 19, 2023	Bayesian InferenceDenoising	CodeCode Available	0
Individual Fairness in Bayesian Neural Networks	Apr 21, 2023	Adversarial RobustnessBayesian Inference	CodeCode Available	0
Semi-Modular Inference: enhanced learning in multi-modular models by tempering the influence of components	Mar 15, 2020	Bayesian InferenceMeta-Learning	CodeCode Available	0
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings	Feb 27, 2017	Bayesian InferenceClassification	CodeCode Available	0
Inference of a mesoscopic population model from population spike trains	Oct 3, 2019	Bayesian Inference	CodeCode Available	0
Parsimony-Enhanced Sparse Bayesian Learning for Robust Discovery of Partial Differential Equations	Jul 8, 2021	Bayesian InferenceModel Selection	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