The Rise of Uncertainty Quantification in Deep Learning

This article, from 2016, highlights a critical, early discussion regarding uncertainty quantification within deep learning models, a field that has since seen significant advancements. The focus on uncertainty reflects an important move toward more robust and reliable AI systems.

• •Uncertainty quantification is crucial for building trustworthy AI.
• •Early research in the field laid the groundwork for future progress.
• •Addressing uncertainty improves model reliability and robustness.