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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 331–340 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
Deep Active Inference as Variational Policy Gradients	Jul 8, 2019	Bayesian Inferencereinforcement-learning	CodeCode Available	0	5
Measuring Uncertainty through Bayesian Learning of Deep Neural Network Structure	Nov 22, 2019	Bayesian InferenceNeural Architecture Search	CodeCode Available	0	5
A Mutually-Dependent Hadamard Kernel for Modelling Latent Variable Couplings	Feb 27, 2017	Bayesian InferenceClassification	CodeCode Available	0	5
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	CodeCode Available	0	5
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal Inference	CodeCode Available	0	5
Bayesian adaptive and interpretable functional regression for exposure profiles	Mar 1, 2022	Bayesian Inferenceregression	CodeCode Available	0	5
Data-driven Approach for Interpolation of Sparse Data	May 2, 2025	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
deBInfer: Bayesian inference for dynamical models of biological systems in R	Oct 15, 2016	Bayesian Inference	CodeCode Available	0	5
Deep Learning and genetic algorithms for cosmological Bayesian inference speed-up	May 6, 2024	Bayesian InferenceHyperparameter Optimization	CodeCode Available	0	5
Detecting Model Misspecification in Amortized Bayesian Inference with Neural Networks	Dec 16, 2021	Bayesian InferenceDecision Making	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