Why Use Uncertainty Quantification

Summary

Presenter: Sang-ri Yi, University of California, Berkeley This session covers brief introductions to the SimCenter and the quoFEM ... What if your AI model could tell you not just what will happen — but how sure it is? MCML PI David Rügamer explains why ... 2025 ML Academy & Artiste Distinguished Lecture. Gaussian process regression (GPR) is a probabilistic approach to making predictions. GPRs are easy to implement, flexible, and ... Measuring Doubt in Systems That Have None: In this SEI Podcast, Dr. Eric Heim, a senior machine learning research scientist at the Software Engineering Institute at Carnegie ... The significance of predicting the glass transition temperature (Tg) of polymers lies in its critical role in determining how materials ...