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stat.ML2017
Non-linear reduced modeling of dynamical systems using kernel methods and low-rank approximation
Patrick Héas, Cédric Herzet, Benoit Combès
Reduced modeling of a computationally demanding dynamical system aims at approximating its trajectories, while optimizing the trade-off between accuracy and computational complexit…
stat.ML2016
Low-Rank Dynamic Mode Decomposition: An Exact and Tractable Solution
Patrick Héas, Cédric Herzet
This work studies the linear approximation of high-dimensional dynamical systems using low-rank dynamic mode decomposition (DMD). Searching this approximation in a data-driven appr…