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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 2051–2060 of 2226 papers

Title	Date	Tasks	Status	Hype
Sampling with Trusthworthy Constraints: A Variational Gradient Framework	May 21, 2021	Bayesian InferenceFairness	CodeCode Available	0
A stochastic Stein Variational Newton method	Apr 19, 2022	Bayesian Inference	CodeCode Available	0
Scalable approximate Bayesian inference for particle tracking data	Jul 1, 2018	Bayesian Inference	CodeCode Available	0
Normalizing Constant Estimation with Gaussianized Bridge Sampling	Dec 12, 2019	Bayesian Inference	CodeCode Available	0
The Neural Moving Average Model for Scalable Variational Inference of State Space Models	Oct 2, 2019	Bayesian InferenceNormalising Flows	CodeCode Available	0
NFAD: Fixing anomaly detection using normalizing flows	Dec 19, 2019	Anomaly DetectionBayesian Inference	CodeCode Available	0
Not All Claims are Created Equal: Choosing the Right Statistical Approach to Assess Hypotheses	Nov 10, 2019	AllBayesian Inference	CodeCode Available	0
Assumed Density Filtering Q-learning	Dec 9, 2017	Atari GamesBayesian Inference	CodeCode Available	0
Scalable Bayesian Inference for Excitatory Point Process Networks	Jul 12, 2015	Bayesian InferenceVariational Inference	CodeCode Available	0
Object proposal generation applying the distance dependent Chinese restaurant process	Apr 12, 2017	Bayesian InferenceObject	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