Paper of Stefan Klus on a Python library for machine learning published in “Machine Learning: Science and Technology”

The paper “Deeptime: a Python library for machine learning dynamical models from time series data“, co-authored by Moritz Hoffmann (Free U Berlin), Martin Scherer (Free U Berlin), Tim Hempel (Free U Berlin), Andreas Mardt (Free U Berlin), Brian de Silva (University of Washington), Brooke E Husic (Free U Berlin & Princeton University), Stefan Klus, Hao Wu (Tongji University, Shanghai), Nathan Kutz (University of Washington), Steven L Brunton (University of Washington), has been published in the IOP Journal Machine Learning: Science and Technology. The paper is published gold open access (link here). The image below shows relationships of conventional dimension reduction. See figures 2,3 and 8 for the authors proposed new strategies. The Python toolbox and documentation can be foundĀ here.

Figure 1 from paper