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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 1211–1220 of 2226 papers

TitleStatusHype
Variational Density Propagation Continual Learning—0
Variational Domain Adaptation—0
Variational Gaussian Dropout is not Bayesian—0
Variational Hamiltonian Monte Carlo via Score Matching—0
Variational Inference as Iterative Projection in a Bayesian Hilbert Space with Application to Robotic State Estimation—0
Variational Inference for Bayesian Bridge Regression—0
Variational Inference for GARCH-family Models—0
Variational Inference for Gaussian Process Modulated Poisson Processes—0
Variational Inference for Latent Variable Models in High Dimensions—0
Variational Inference for Model-Free and Model-Based Reinforcement Learning—0
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Benchmark Results

#ModelMetricClaimedVerifiedStatus
1F-SWAAccuracy83.61—Unverified
2F-SWAGAccuracy80.93—Unverified