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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 1441–1450 of 2226 papers

TitleStatusHype
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
Variational Inference for Quantum HyperNetworks—0
Variational Inference for Sparse and Undirected Models—0
Theoretical Guarantees for Variational Inference with Fixed-Variance Mixture of Gaussians—0
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Benchmark Results

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