The sixty-second UQSay seminar on UQ, DACE and related topics will take place online on Thursday afternoon, October 5, 2023.
2–3 PM — Sibo Cheng (Data Science Inst., Imperial College London) — [slides]
Machine learning and data assimilation for high dimensional dynamical systems
Data Assimilation (DA) and Machine Learning (ML) methods are extensively used in predicting and updating high-dimensional spatial-temporal dynamics. Typical applications span from computational fluid dynamics to geoscience and climate systems. In recent years, much effort has been given in combining DA and ML techniques with objectives including but not limited to dynamical system identification, reduced order surrogate modelling, error covariance specification and model error correction. This talk will provide an overview of state-of-the-art research in this interdisciplinary field, covering a wide range of applications. I will also present my unpublished work regarding efficient deep data assimilation with sparse observations and time-varying sensors. The proposed method, incorporating a deep learning inverse operator based on Voronoi tessellation into the assimilation objective function, is adept at handling sparse, unstructured, and time-varying sensor data.
Reference: S. Cheng, C. Quilodran-Casas, S. Ouala, A. Farchi, C. Liu, P. Tandeo, R. Fablet, D. Lucor, B. Iooss, J. Brajard, D. Xiao, T. Janjic, W. Ding, Y. Guo, A. Carrassi, M. Bocquet and R. Arcucci, “Machine Learning With Data Assimilation and Uncertainty Quantification for Dynamical Systems: A Review”, IEEE/CAA Journal of Automatica Sinica, vol. 10, no. 6, pp. 1361–1387, June 2023.
Organizing committee: Pierre Barbillon (MIA-Paris), Julien Bect (L2S), Nicolas Bousquet (EDF R&D), Amélie Fau (LMPS), Filippo Gatti (LMPS), Bertrand Iooss (EDF R&D), Alexandre Janon (LMO), Sidonie Lefebvre (ONERA), Didier Lucor (LISN), Emmanuel Vazquez (L2S).
Coordinators: Julien Bect (L2S) & Sidonie Lefebvre (ONERA)
Practical details: the seminar will be held online using Microsoft Teams.
If you want to attend this seminar (or any of the forthcoming online UQSay seminars), and if you do not already have access to the UQSay group on Teams, simply send an email and you will be invited. Please specify which email address the invitation must be sent to (this has to be the address associated with your Teams account).
You will find the link to the seminar on the "General" UQSay channel on Teams, approximately 15 minutes before the beginning.
The technical side of things: you can use Teams either directly from your web browser or using the "fat client", which is available for most platforms (Windows, Linux, Mac, Android & iOS). We strongly recommend the latter option whenever possible. Please give it a try before the seminar to anticipate potential problems.
