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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 171–180 of 2226 papers

Title	Date	Tasks	Status	Hype
Probabilistic Autoencoder	Jun 9, 2020	Bayesian InferenceDenoising	CodeCode Available	1
Variational Auto-Regressive Gaussian Processes for Continual Learning	Jun 9, 2020	Bayesian InferenceContinual Learning	CodeCode Available	1
Bayesian Adversarial Human Motion Synthesis	Jun 1, 2020	Bayesian InferenceData Augmentation	CodeCode Available	1
Bayesian differential programming for robust systems identification under uncertainty	Apr 15, 2020	Bayesian InferenceModel Discovery	CodeCode Available	1
A Practical Introduction to Bayesian Estimation of Causal Effects: Parametric and Nonparametric Approaches	Apr 15, 2020	Bayesian InferenceCausal Inference	CodeCode Available	1
Inferring COVID-19 spreading rates and potential change points for case number forecasts	Apr 2, 2020	Bayesian Inference	CodeCode Available	1
Supervised Learning with Quantum Measurements	Apr 2, 2020	Bayesian InferenceGeneral Classification	CodeCode Available	1
GAN-based Priors for Quantifying Uncertainty	Mar 27, 2020	Bayesian InferenceDenoising	CodeCode Available	1
Too many cooks: Bayesian inference for coordinating multi-agent collaboration	Mar 26, 2020	Bayesian Inference	CodeCode Available	1
BayesFlow: Learning complex stochastic models with invertible neural networks	Mar 13, 2020	Bayesian InferenceEpidemiology	CodeCode Available	1

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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