Tag: Outlier detection
-
Decision Theory for Large-Scale Outlier Detection Using Aleatoric Uncertainty
The content discusses aleatoric uncertainty in Bayesian neural networks and its application to outlier detection. By leveraging decision theory, the author explores how modeling uncertainties in parameters and data generating mechanisms can enhance outlier classification. This involves formulating loss functions and employing Bayesian false discovery rate strategies for effective threshold setting.