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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 2101–2110 of 2226 papers

Title	Date	Tasks	Status	Hype
Quasi-Bayesian Dual Instrumental Variable Regression	Jun 16, 2021	Bayesian Inferenceregression	CodeCode Available	0
Learning to infer in recurrent biological networks	Jun 18, 2020	Bayesian InferenceVariational Inference	CodeCode Available	0
Arbitrary Marginal Neural Ratio Estimation for Simulation-based Inference	Oct 1, 2021	Bayesian Inference	CodeCode Available	0
On the relationship between a Gamma distributed precision parameter and the associated standard deviation in the context of Bayesian parameter inference	Jan 15, 2021	Bayesian Inference	CodeCode Available	0
Scalable Semi-Modular Inference with Variational Meta-Posteriors	Apr 1, 2022	Bayesian InferenceMeta-Learning	CodeCode Available	0
A Probabilistic Disease Progression Model for Predicting Future Clinical Outcome	Mar 13, 2018	Bayesian Inference	CodeCode Available	0
Scalable Stochastic Gradient Riemannian Langevin Dynamics in Non-Diagonal Metrics	Mar 9, 2023	Bayesian Inference	CodeCode Available	0
SuperARC: An Agnostic Test for Narrow, General, and Super Intelligence Based On the Principles of Recursive Compression and Algorithmic Probability	Mar 20, 2025	Bayesian Inference	CodeCode Available	0
On the representation and learning of monotone triangular transport maps	Sep 22, 2020	Bayesian InferenceDensity Estimation	CodeCode Available	0
A Bayesian Method for Joint Clustering of Vectorial Data and Network Data	Oct 24, 2017	Bayesian InferenceClustering	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