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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 1881–1890 of 2226 papers

Title	Date	Tasks	Status	Hype
An efficient likelihood-free Bayesian inference method based on sequential neural posterior estimation	Nov 21, 2023	Bayesian Inference	CodeCode Available	0
Analytic solution and stationary phase approximation for the Bayesian lasso and elastic net	Sep 25, 2017	Bayesian Inferenceregression	CodeCode Available	0
Microbiome subcommunity learning with logistic-tree normal latent Dirichlet allocation	Sep 11, 2021	Bayesian Inference	CodeCode Available	0
Estimating Idea Production: A Methodological Survey	May 17, 2024	Bayesian InferenceSurvey	CodeCode Available	0
A Metaheuristic for Amortized Search in High-Dimensional Parameter Spaces	Sep 28, 2023	Bayesian Inference	CodeCode Available	0
Estimating Risk and Uncertainty in Deep Reinforcement Learning	May 23, 2019	Bayesian InferenceDeep Reinforcement Learning	CodeCode Available	0
Mind the GAP: Improving Robustness to Subpopulation Shifts with Group-Aware Priors	Mar 14, 2024	AttributeBayesian Inference	CodeCode Available	0
Unifying Summary Statistic Selection for Approximate Bayesian Computation	Jun 6, 2022	Bayesian InferenceDimensionality Reduction	CodeCode Available	0
Etalumis: Bringing Probabilistic Programming to Scientific Simulators at Scale	Jul 8, 2019	Bayesian InferenceCPU	CodeCode Available	0
Evaluating and Modeling Social Intelligence: A Comparative Study of Human and AI Capabilities	May 20, 2024	Bayesian InferenceZero-Shot Learning	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