Introduction to Deep Evidential Regression for Uncertainty Quantification

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Introduction to Deep Evidential Regression for Uncertainty Quantification

Machine learning models can be confident even when they shouldn’t be. This article introduces Deep Evidential Regression (DER), a method that lets neural networks rapidly express what they don’t know.

The post Introduction to Deep Evidential Regression for Uncertainty Quantification appeared first on Towards Data Science.

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