Conformal prediction offers a robust, distribution-free framework that transforms point estimates into prediction sets or intervals by leveraging the concept of exchangeability. This framework helps ...

The newest journal from the Society for Industrial and Applied Mathematics, SIAM/ASA Journal on Uncertainty Quantification (JUQ), launched today with its first seven papers publishing online to Volume ...

Improving uncertainty quantification in LLMs, this method combines epistemic and aleatoric uncertainty, leading to better ...

Dr. Doostan's research team is focused on the development of novel theories and numerical tools to rigorously tackle several grand challenges associated with Uncertainty Quantification (UQ) and ...

A course in Uncertainty Quantification with an emphasis on formulating and computation to extract predictions and uncertainty in computational and simulation models ...

Abstract: Scientists and engineers use computer simulations to study relationships between a physical model’s input parameters and its output predictions. However, thorough parameter studies---e.g., ...

Professor Edmund Lam, Dr Ni Chen and their research team from the Department of Electrical and Electronic Engineering under the Faculty of Engineering at the University of Hong Kong (HKU) have ...

Although artificial intelligence (AI) has demonstrated potential in automating glaucoma screening, there is still a ...