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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 1461–1470 of 2226 papers

Title	Date	Tasks	Status	Hype
Development of Use-specific High Performance Cyber-Nanomaterial Optical Detectors by Effective Choice of Machine Learning Algorithms	Dec 26, 2019	Bayesian Inference	CodeCode Available	0
Attention-Aware Answers of the Crowd	Dec 24, 2019	Bayesian Inference	—Unverified	0
Blang: Bayesian declarative modelling of general data structures and inference via algorithms based on distribution continua	Dec 22, 2019	Bayesian Inference	CodeCode Available	0
Quantile Propagation for Wasserstein-Approximate Gaussian Processes	Dec 21, 2019	Bayesian InferenceGaussian Processes	CodeCode Available	0
NFAD: Fixing anomaly detection using normalizing flows	Dec 19, 2019	Anomaly DetectionBayesian Inference	CodeCode Available	0
Normalizing Constant Estimation with Gaussianized Bridge Sampling	Dec 12, 2019	Bayesian Inference	CodeCode Available	0
Diagnosing model misspecification and performing generalized Bayes' updates via probabilistic classifiers	Dec 12, 2019	Bayesian InferenceDiagnostic	—Unverified	0
On the relationship between multitask neural networks and multitask Gaussian Processes	Dec 12, 2019	Bayesian InferenceGaussian Processes	—Unverified	0
A Closer Look at Disentangling in β-VAE	Dec 11, 2019	Bayesian InferenceVariational Inference	—Unverified	0
Hidden Markov Model: Tutorial	Dec 10, 2019	Action RecognitionBayesian 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