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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 91–100 of 2226 papers

Title	Date	Tasks	Status	Hype
Laplacian Autoencoders for Learning Stochastic Representations	Jun 30, 2022	Bayesian InferenceOut-of-Distribution Detection	CodeCode Available	1
Personalized Federated Learning via Variational Bayesian Inference	Jun 16, 2022	Bayesian InferenceDiversity	CodeCode Available	1
Scalable Deep Gaussian Markov Random Fields for General Graphs	Jun 10, 2022	Bayesian InferenceVariational Inference	CodeCode Available	1
Fast Bayesian Inference with Batch Bayesian Quadrature via Kernel Recombination	Jun 9, 2022	Bayesian InferenceNumerical Integration	CodeCode Available	1
Variational inference via Wasserstein gradient flows	May 31, 2022	Bayesian InferenceVariational Inference	CodeCode Available	1
Marginal Post Processing of Bayesian Inference Products with Normalizing Flows and Kernel Density Estimators	May 25, 2022	Bayesian InferenceExperimental Design	CodeCode Available	1
Zero-Shot Logit Adjustment	Apr 25, 2022	Bayesian InferenceGeneralized Zero-Shot Learning	CodeCode Available	1
The Boltzmann Policy Distribution: Accounting for Systematic Suboptimality in Human Models	Apr 22, 2022	Bayesian InferenceImitation Learning	CodeCode Available	1
A Framework for Improving the Reliability of Black-box Variational Inference	Mar 29, 2022	Bayesian InferenceStochastic Optimization	CodeCode Available	1
Knowledge Removal in Sampling-based Bayesian Inference	Mar 24, 2022	Bayesian InferenceMachine Unlearning	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