2 papers
cs.LG2025
How deep is your network? Deep vs. shallow learning of transfer operators
Mohammad Tabish, Benedict Leimkuhler, Stefan Klus
We propose a randomized neural network approach called RaNNDy for learning transfer operators and their spectral decompositions from data. The weights of the hidden layers of the n…
math.DS2025
Learning dynamical systems from data: Gradient-based dictionary optimization
Mohammad Tabish, Neil K. Chada, Stefan Klus
The Koopman operator plays a crucial role in analyzing the global behavior of dynamical systems. Existing data-driven methods for approximating the Koopman operator or discovering…