12 citations · 12 across the 4 of their papers we have counts for
5 papers
Multiscale Decomposition Reveals Predictable Interannual Variability and Climate Trends in Antarctic Sea Ice Loss
Peter Yatsyshin, Karl Lapo, Jonathan Smith +4
Antarctic sea ice has undergone unprecedented changes in recent years, raising questions about how this key geophysical system is responding to climate change. Decades of slow expa…
An Interpretable Data-Driven Model of the Flight Dynamics of Hawks
Lydia France, Karl Lapo, J. Nathan Kutz
Despite significant analysis of bird flight, generative physics models for flight dynamics do not currently exist. Yet the underlying mechanisms responsible for various flight mano…
Phasor notation of Dynamic Mode Decomposition
Karl Lapo, Samuele Mosso, J. Nathan Kutz
Dynamic Mode Decomposition (DMD) is a powerful, data-driven method for diagnosing complex dynamics. Various DMD algorithms allow one to fit data with a low-rank model that decompos…
Unsupervised multi-scale diagnostics
Karl Lapo, Sara M. Ichinaga, Nathan Kutz
The unsupervised and principled diagnosis of multi-scale data is a fundamental obstacle in modern scientific problems from, for instance, weather and climate prediction, neurology,…
PyDMD: A Python package for robust dynamic mode decomposition
Sara M. Ichinaga, Francesco Andreuzzi, Nicola Demo +5
The dynamic mode decomposition (DMD) is a simple and powerful data-driven modeling technique that is capable of revealing coherent spatiotemporal patterns from data. The method's l…