Understanding Uncertainty Quantification In Machine Learning
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- 2025 ML Academy & Artiste Distinguished Lecture.
- In this SEI Podcast, Dr. Eric Heim, a senior
- ... we explore the concept of
- A brief overview of
- Speaker: Professor Eyke Hüllermeier (LMU) Titel:
Detailed Analysis of Uncertainty Quantification In Machine Learning
Gaussian process regression (GPR) is a probabilistic approach to making predictions. GPRs are easy to implement, flexible, and ... Neural networks are infamous for making wrong predictions with high confidence. Ideally, when a model encounters difficult ... Presented at the Argonne Training Program on Extreme-Scale Computing 2019. Slides for this presentation are available here: ...
A quick 20 min introduction to various UQ methods for
That wraps up our extensive overview of Uncertainty Quantification In Machine Learning.
