Learning dynamical systems through operator-theoretic representations provides a powerful framework for analyzing complex dynamics, as spectral quantities such as eigenvalues and …
The geometry of dynamical systems estimated from trajectory data is a major chal- lenge for machine learning applications. Koopman and transfer operators provide a linear …
Lorem ipsum dolor sit amet, consectetur adipiscing elit. Duis posuere tellus ac convallis placerat. Proin tincidunt magna sed ex sollicitudin condimentum.
Motif Discovery consists of finding repeated patterns and locating their occurrences in a time series without prior knowledge about their shape or location. Most state-of-the-art …