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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 1961–1970 of 2226 papers

Title	Date	Tasks	Status	Hype
Multilevel neural simulation-based inference	Jun 6, 2025	Bayesian Inference	CodeCode Available	0
Fidelity of Hyperbolic Space for Bayesian Phylogenetic Inference	Jun 16, 2022	Bayesian InferenceNavigate	CodeCode Available	0
Fine-Tuning Generative Models as an Inference Method for Robotic Tasks	Oct 19, 2023	Bayesian InferenceGPU	CodeCode Available	0
Bayesian inference via sparse Hamiltonian flows	Mar 11, 2022	Bayesian Inference	CodeCode Available	0
Robust and Conjugate Gaussian Process Regression	Nov 1, 2023	Bayesian InferenceBayesian Optimisation	CodeCode Available	0
Robust and Scalable Variational Bayes	Apr 16, 2025	Bayesian Inference	CodeCode Available	0
MultiNest: an efficient and robust Bayesian inference tool for cosmology and particle physics	Sep 19, 2008	Bayesian Inference	CodeCode Available	0
Robust Anytime Learning of Markov Decision Processes	May 31, 2022	Bayesian InferenceDecision Making	CodeCode Available	0
Fitting A Mixture Distribution to Data: Tutorial	Jan 20, 2019	Bayesian InferenceBayesian Optimisation	CodeCode Available	0
Fixed-kinetic Neural Hamiltonian Flows for enhanced interpretability and reduced complexity	Feb 3, 2023	Bayesian Inference	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