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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 1171–1180 of 2226 papers

Title	Date	Tasks	Status	Hype
Neural Sampling Machine with Stochastic Synapse allows Brain-like Learning and Inference	Feb 20, 2021	Bayesian InferenceDecision Making	—Unverified	0
Trumpets: Injective Flows for Inference and Inverse Problems	Feb 20, 2021	Bayesian InferenceImage Reconstruction	CodeCode Available	1
Estimating the impact of non-pharmaceutical interventions and vaccination on the progress of the COVID-19 epidemic in Mexico: a mathematical approach	Feb 19, 2021	Bayesian Inference	—Unverified	0
The Variational Bayesian Inference for Network Autoregression Models	Feb 18, 2021	Bayesian InferenceComputational Efficiency	—Unverified	0
Structured Dropout Variational Inference for Bayesian Neural Networks	Feb 16, 2021	Bayesian InferenceComputational Efficiency	—Unverified	0
Neural Posterior Regularization for Likelihood-Free Inference	Feb 15, 2021	Bayesian Inference	CodeCode Available	0
ScrofaZero: Mastering Trick-taking Poker Game Gongzhu by Deep Reinforcement Learning	Feb 15, 2021	Bayesian InferenceDeep Reinforcement Learning	CodeCode Available	0
Scalable Bayesian Inverse Reinforcement Learning	Feb 12, 2021	Bayesian InferenceImitation Learning	CodeCode Available	1
Projected Wasserstein gradient descent for high-dimensional Bayesian inference	Feb 12, 2021	Bayesian InferenceDensity Estimation	CodeCode Available	0
Bayesian Inference with Certifiable Adversarial Robustness	Feb 10, 2021	Adversarial RobustnessBayesian Inference	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