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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 271–280 of 2226 papers

Title	Date	Tasks	Status	Hype	Score
A Bayesian Method for Joint Clustering of Vectorial Data and Network Data	Oct 24, 2017	Bayesian InferenceClustering	CodeCode Available	0	5
Deep Bayesian inference for seismic imaging with tasks	Oct 10, 2021	Bayesian InferenceInductive Bias	CodeCode Available	0	5
Data Subsampling for Bayesian Neural Networks	Oct 17, 2022	Bayesian InferenceFederated Learning	CodeCode Available	0	5
Accelerating Convergence of Stein Variational Gradient Descent via Deep Unfolding	Feb 23, 2024	Bayesian InferenceVariational Inference	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 Dirichlet Mixture Model of Hawkes Processes for Event Sequence Clustering	Jan 31, 2017	Bayesian InferenceClustering	CodeCode Available	0	5
Data-driven Approach for Interpolation of Sparse Data	May 2, 2025	Bayesian InferenceGaussian Processes	CodeCode Available	0	5
Debiased Bayesian inference for average treatment effects	Sep 26, 2019	Bayesian InferenceCausal Inference	CodeCode Available	0	5
A digital twin framework for civil engineering structures	Aug 2, 2023	Bayesian InferenceCantilever Beam	CodeCode Available	0	5
CrossCat: A Fully Bayesian Nonparametric Method for Analyzing Heterogeneous, High Dimensional Data	Dec 3, 2015	Bayesian InferenceCommon Sense Reasoning	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