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Predictive data science for physical systems- From model reduction to scientific machine learning
Presenter
- Karen Willcox
February 20, 2020
ICERM
Model reduction for port-Hamiltonian differential-algebraic systems
Presenter
- Volker Mehrmann
February 20, 2020
ICERM
A Rank-Minimization Approach to Learning Dynamical Systems from Frequency Response Data
Presenter
- Pawan Goyal
February 20, 2020
ICERM
Convolutional autoencoders and LSTMs - using deep learning to overcome Kolmogorov-width limitations and accurately model errors in nonlinear model reduction
Presenter
- Kevin Carlberg
February 21, 2020
ICERM
New strategies for reduced-order models for predicting the statistical responses and uncertainty quantification in complex turbulent dynamical systems
Presenter
- Andrew Majda
January 11, 2017
IPAM
Learning dynamics with dynamical distances: From diffusion maps to commute maps and coherence
Presenter
- Ralf Banisch
December 5, 2016
IPAM
A brief review of progress and some remaining challenges in modelling plant development
Presenter
- Vince Gutschick
October 1, 2010
MBI
Tensor numerical modeling of the collective electrostatic potentials in many-particle systems
Presenter
- Venera Khoromskaia
May 4, 2021
IPAM