Uncertainty Quantification Machine Learning

Summary

2025 ML Academy & Artiste Distinguished Lecture. Predictions from modeling and simulation (M&S) are increasingly relied upon to inform critical decision making in a variety of ... Neural networks are infamous for making wrong predictions with high confidence. Ideally, when a model encounters difficult ... Gaussian process regression (GPR) is a probabilistic approach to making predictions. GPRs are easy to implement, flexible, and ... What if your AI model could tell you not just what will happen — but how sure it is? MCML PI David Rügamer explains why ... A quick 20 min introduction to various UQ methods for Deep Presented at the Argonne Training Program on Extreme-Scale Computing 2019. Slides for this presentation are available here: ... In seismic inverse problems, the noise and illumination configuration severely impact the interpretation of the subsurface. Roger Ghanem is Professor of Civil and Environmental Engineering at the U of Southern California where he also holds the Tryon ... Virtual poster presentation for Decoding the Brain @ MLSP. The full paper can be found on arXiv. It is well known that accurate probabilistic predictors can be trained through empirical risk minimisation with proper scoring rules ...