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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 1631–1640 of 2226 papers

Title	Date	Tasks	Status	Hype
Functional Variational Bayesian Neural Networks	Mar 14, 2019	Bayesian InferenceGaussian Processes	CodeCode Available	0
A Multi-armed Bandit MCMC, with applications in sampling from doubly intractable posterior	Mar 13, 2019	Bayesian Inference	—Unverified	0
Elements of Sequential Monte Carlo	Mar 12, 2019	Bayesian InferenceBIG-bench Machine Learning	—Unverified	0
Goal-Directed Behavior under Variational Predictive Coding: Dynamic Organization of Visual Attention and Working Memory	Mar 12, 2019	Bayesian Inference	—Unverified	0
Embarrassingly parallel MCMC using deep invertible transformations	Mar 11, 2019	Bayesian Inference	—Unverified	0
Spiking Neural Network on Neuromorphic Hardware for Energy-Efficient Unidimensional SLAM	Mar 6, 2019	Bayesian InferenceCPU	—Unverified	0
V2X System Architecture Utilizing Hybrid Gaussian Process-based Model Structures	Mar 4, 2019	Bayesian InferenceGaussian Processes	—Unverified	0
Joint Perception and Control as Inference with an Object-based Implementation	Mar 4, 2019	Bayesian InferenceDecision Making	—Unverified	0
Approximation Properties of Variational Bayes for Vector Autoregressions	Mar 2, 2019	Bayesian Inferenceregression	—Unverified	0
Adaptive Gaussian Copula ABC	Feb 27, 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