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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 1871–1880 of 2226 papers

Title	Date	Tasks	Status	Hype
Ensemble transport smoothing. Part II: Nonlinear updates	Oct 31, 2022	Bayesian InferenceState Space Models	CodeCode Available	0
Baxter Permutation Process	Dec 1, 2020	Bayesian Inference	CodeCode Available	0
Bayesian Learning-Based Adaptive Control for Safety Critical Systems	Oct 5, 2019	Autonomous VehiclesBayesian Inference	CodeCode Available	0
Metric Gaussian Variational Inference	Jan 30, 2019	Bayesian InferenceVariational Inference	CodeCode Available	0
Epidemic-guided deep learning for spatiotemporal forecasting of Tuberculosis outbreak	Feb 15, 2025	Bayesian InferenceConformal Prediction	CodeCode Available	0
A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference	Jan 8, 2019	Bayesian InferenceGeneral Classification	CodeCode Available	0
Stacking for Non-mixing Bayesian Computations: The Curse and Blessing of Multimodal Posteriors	Jun 22, 2020	Bayesian Inferenceregression	CodeCode Available	0
A Compact Representation for Bayesian Neural Networks By Removing Permutation Symmetry	Dec 31, 2023	Bayesian InferenceVariational Inference	CodeCode Available	0
Challenges in Markov chain Monte Carlo for Bayesian neural networks	Oct 15, 2019	Bayesian Inferencevalid	CodeCode Available	0
Variational methods for simulation-based inference	Mar 8, 2022	Bayesian InferenceVariational 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