.. DO NOT MODIFY: this file was automatically generated! :orphan: Seminar by Nan Chen ================================= .. container:: sd-badge-seminar-container :bdg-primary-line:`Speaker` .. container:: sd-badge-next-text Nan Chen (University of Wisconsin-Madison) :bdg-primary-line:`Title` .. container:: sd-badge-next-text Stochastic and Statistical Reduced-Order Models :bdg-primary-line:`Date` .. container:: sd-badge-next-text * October 31, 2023 15:00 CET+0100 (Europe/Rome) * October 31, 2023 10:00 EDT-0400 (US/Eastern) * October 31, 2023 09:00 CDT-0500 (US/Central) * October 31, 2023 07:00 PDT-0700 (US/Pacific) :bdg-primary-line:`Abstract` .. container:: sd-badge-next-text In this talk, I will give an introduction to the stochastic and the statistical reduced-order models. These reduced-order models play an essential role in facilitating the computations of many scientific problems in geophysics, engineering, neuroscience, material science, etc. They also advance the understanding of key physics. I will start with building various stochastic reduced-order models and present methods to systematically determine these models. I will illustrate their unique features in different applications. Then, I will link these reduced-order models with efficient data assimilation and statistical forecast. Related to these topics, I will discuss statistical reduced-order models, which are quite useful for uncertainty quantification. Finally, I will show one exciting example of how these reduced-order models can reversely help develop more sophisticated physical models that characterize a real atmosphere-ocean phenomenon. :bdg-primary-line:`Recording` .. container:: sd-badge-next-text Watch the recording on `our YouTube channel `_.