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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 511–520 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
A Metalearned Neural Circuit for Nonparametric Bayesian Inference	Nov 24, 2023	Bayesian InferenceInductive Bias	CodeCode Available	0	5
Deep learning and MCMC with aggVAE for shifting administrative boundaries: mapping malaria prevalence in Kenya	May 31, 2023	Bayesian Inference	CodeCode Available	0	5
Automated Scalable Bayesian Inference via Hilbert Coresets	Oct 13, 2017	Bayesian Inference	CodeCode Available	0	5
A Metaheuristic for Amortized Search in High-Dimensional Parameter Spaces	Sep 28, 2023	Bayesian Inference	CodeCode Available	0	5
Deep Neural Networks as Gaussian Processes	Nov 1, 2017	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
Detecting structural perturbations from time series with deep learning	Jun 9, 2020	Bayesian InferenceDeep Learning	CodeCode Available	0	5
deBInfer: Bayesian inference for dynamical models of biological systems in R	Oct 15, 2016	Bayesian Inference	CodeCode Available	0	5
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal Inference	CodeCode Available	0	5
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	CodeCode Available	0	5

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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