SOTAVerified

Bayesian Inference

Bayesian Inference is a methodology that employs Bayes Rule to estimate parameters (and their full posterior).

Papers

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Showing 1051–1060 of 2226 papers

TitleStatusHype
A visual exploration of Gaussian Processes and Infinite Neural Networks—0
Bayesian sense of time in biological and artificial brains—0
An Overview of Uncertainty Quantification Methods for Infinite Neural Networks—0
Spatiotemporal Clustering with Neyman-Scott Processes via Connections to Bayesian Nonparametric Mixture ModelsCode0
SpectraNet: Learned Recognition of Artificial Satellites From High Contrast Spectroscopic Imagery—0
Loss-calibrated expectation propagation for approximate Bayesian decision-making—0
A Novel Incremental Learning Driven Instance Segmentation Framework to Recognize Highly Cluttered Instances of the Contraband ItemsCode0
Classifying Turbulent Environments via Machine Learning—0
Bayesian Invariant Risk Minimization—0
Inferring perceptual decision making parameters from behavior in production and reproduction tasks—0
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Benchmark Results

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