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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 1661–1670 of 2226 papers

Title	Date	Tasks	Status	Hype
Fitting A Mixture Distribution to Data: Tutorial	Jan 20, 2019	Bayesian InferenceBayesian Optimisation	CodeCode Available	0
A bi-partite generative model framework for analyzing and simulating large scale multiple discrete-continuous travel behaviour data	Jan 18, 2019	Bayesian InferenceBIG-bench Machine Learning	—Unverified	0
Theory of Minds: Understanding Behavior in Groups Through Inverse Planning	Jan 18, 2019	Action UnderstandingBayesian Inference	—Unverified	0
Multi-modal Ensemble Classification for Generalized Zero Shot Learning	Jan 15, 2019	Bayesian InferenceClassification	—Unverified	0
Mixed Variational Inference	Jan 15, 2019	Bayesian InferenceVariational Inference	CodeCode Available	0
Bayesian shrinkage in mixture of experts models: Identifying robust determinants of class membership	Jan 12, 2019	Bayesian InferenceMixture-of-Experts	—Unverified	0
Undirected Graphical Models as Approximate Posteriors	Jan 11, 2019	Bayesian Inference	CodeCode Available	0
A Comprehensive guide to Bayesian Convolutional Neural Network with Variational Inference	Jan 8, 2019	Bayesian InferenceGeneral Classification	CodeCode Available	0
Uncertainty-Based Out-of-Distribution Detection in Deep Reinforcement Learning	Jan 8, 2019	Bayesian InferenceDeep Reinforcement Learning	—Unverified	0
Can You Trust This Prediction? Auditing Pointwise Reliability After Learning	Jan 2, 2019	Bayesian Inference	—Unverified	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