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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 1781–1790 of 2226 papers

Title	Date	Tasks	Status	Hype
Distilling Model Knowledge	Oct 8, 2015	Bayesian InferenceBIG-bench Machine Learning	CodeCode Available	0
Conditional Optimal Transport on Function Spaces	Nov 9, 2023	Bayesian Inference	CodeCode Available	0
Probing as Quantifying Inductive Bias	Oct 15, 2021	Bayesian InferenceInductive Bias	CodeCode Available	0
Sparse Algorithms for Markovian Gaussian Processes	Mar 19, 2021	Bayesian InferenceGaussian Processes	CodeCode Available	0
Distributed Markov Chain Monte Carlo Sampling based on the Alternating Direction Method of Multipliers	Jan 29, 2024	Bayesian InferenceDistributed Optimization	CodeCode Available	0
Uncertainty in latent representations of variational autoencoders optimized for visual tasks	Apr 23, 2024	Bayesian InferenceInductive Bias	CodeCode Available	0
Bayesian Neural Networks at Finite Temperature	Apr 8, 2019	Bayesian InferenceModel Selection	CodeCode Available	0
Locally Private Bayesian Inference for Count Models	Mar 22, 2018	Bayesian InferenceLink Prediction	CodeCode Available	0
Sparse online variational Bayesian regression	Feb 24, 2021	Bayesian Inferenceregression	CodeCode Available	0
Bayesian at heart: Towards autonomic outflow estimation via generative state-space modelling of heart rate dynamics	Mar 8, 2023	Bayesian InferenceDecision Making	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