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Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 151–160 of 2226 papers

Title	Date	Tasks	Status	Hype
Automatic Posterior Transformation for Likelihood-Free Inference	May 17, 2019	Bayesian InferenceTime Series	CodeCode Available	1
Daily Forecasting of New Cases for Regional Epidemics of Coronavirus Disease 2019 with Bayesian Uncertainty Quantification	Jul 20, 2020	Bayesian InferenceUncertainty Quantification	CodeCode Available	1
Amortizing intractable inference in large language models	Oct 6, 2023	Bayesian InferenceDiversity	CodeCode Available	1
Deep Bayesian Unsupervised Lifelong Learning	Jun 13, 2021	Bayesian InferenceLifelong learning	CodeCode Available	1
A practical tutorial on Variational Bayes	Mar 1, 2021	Bayesian InferenceVariational Inference	CodeCode Available	1
Diffusion Models With Learned Adaptive Noise	Dec 20, 2023	Bayesian InferenceDensity Estimation	CodeCode Available	1
Neural Clustering Processes	Dec 28, 2018	Bayesian InferenceClustering	CodeCode Available	1
Discriminative Training of VBx Diarization	Oct 4, 2023	Bayesian Inference	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
A Primer on Bayesian Neural Networks: Review and Debates	Sep 28, 2023	Bayesian Inference	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