2 citations · 4 across the 5 of their papers we have counts for
5 papers
Convergent Methods for Koopman Operators on Reproducing Kernel Hilbert Spaces
Nicolas Boullé, Matthew J. Colbrook, Gustav Conradie
Data-driven spectral analysis of Koopman operators is a powerful tool for understanding numerous real-world dynamical systems, from neuronal activity to variations in sea surface t…
Decoding complexity: how machine learning is redefining scientific discovery
Ricardo Vinuesa, Paola Cinnella, Jean Rabault +10
As modern scientific instruments generate vast amounts of data and the volume of information in the scientific literature continues to grow, machine learning (ML) has become an ess…
SINDy with Control: A Tutorial
Urban Fasel, Eurika Kaiser, J. Nathan Kutz +2
Many dynamical systems of interest are nonlinear, with examples in turbulence, epidemiology, neuroscience, and finance, making them difficult to control using linear approaches. Mo…
PySensors: A Python Package for Sparse Sensor Placement
Brian M. de Silva, Krithika Manohar, Emily Clark +3
PySensors is a Python package for selecting and placing a sparse set of sensors for classification and reconstruction tasks. Specifically, PySensors implements algorithms for data-…
Sparse-TDA: Sparse Realization of Topological Data Analysis for Multi-Way Classification
Wei Guo, Krithika Manohar, Steven L. Brunton +1
Topological data analysis (TDA) has emerged as one of the most promising techniques to reconstruct the unknown shapes of high-dimensional spaces from observed data samples. TDA, th…