MEAM Ph.D. Thesis Defense: “Deep Learning and Uncertainty Quantification: Methodologies and Applications”
MEAM Ph.D. Thesis Defense: “Deep Learning and Uncertainty Quantification: Methodologies and Applications”
Uncertainty quantification is a recent emerging interdisciplinary area that leverages the power of statistical methods, machine learning models, numerical methods and data-driven approach to provide reliable inference for quantities of interest in natural science and engineering problems. In practice, the sources of uncertainty come from different aspects such as: aleatoric uncertainty where the uncertainty comes […]