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Found 2 papers, 1 papers with code
Beta quantile regression for robust estimation of uncertainty in the presence of outliers
Outlier features can compromise the performance of deep learning regression problems such as style translation, image reconstruction, and deep anomaly detection, potentially leading to misleading conclusions.
Deep Quantile Regression for Uncertainty Estimation in Unsupervised and Supervised Lesion Detection
Here we address the problem of quantifying uncertainty in the images that are reconstructed by the VAE as the basis for principled outlier or lesion detection.
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