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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 1621–1630 of 2226 papers

TitleStatusHype
Compressed sensing reconstruction using Expectation Propagation—0
A Generalization Bound for Online Variational Inference—0
Bayesian Neural Networks at Finite TemperatureCode0
The Kikuchi Hierarchy and Tensor PCA—0
Generalized Variational Inference: Three arguments for deriving new PosteriorsCode0
Robust Optimisation Monte CarloCode0
Learning Personalized Thermal Preferences via Bayesian Active Learning with Unimodality Constraints—0
Pairwise Comparisons with Flexible Time-DynamicsCode0
Combining Model and Parameter Uncertainty in Bayesian Neural NetworksCode0
Weighted Mean Curvature—0
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Benchmark Results

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