4 papers
Weak Dominant Balance for Robust Identification of Dynamically Consistent Fluid Flow Structure
Samuel Ahnert, Esther Lagemann, H. Jane Bae +4
Extracting interpretable, localized physical mechanisms from complex spatiotemporal data is a foundational challenge across physics, biology, and engineering, but has remained out…
Learning Individual Dynamics from Sparse Cross-Sectional Snapshots
Christian Lagemann, Kai Lagemann, Steven L. Brunton +1
Predicting how a dynamical unit evolves over time - how an individual ages, an epidemic spreads, or a physical system degrades - typically requires dense longitudinal tracking. Whe…
The HydroGym Reinforcement Learning Platform for Fluid Dynamics
Christian Lagemann, Sajeda Mokbel, Miro Gondrum +18
Modeling and controlling fluids is critical across science and engineering. Effective flow control can increase lift, reduce drag, enhance mixing, and attenuate noise, potentially…
A deep learning approach to wall-shear stress quantification: From numerical training to zero-shot experimental application
Esther Lagemann, Julia Roeb, Steven L. Brunton +1
The accurate quantification of wall-shear stress dynamics is of substantial importance for various applications in fundamental and applied research, spanning areas from human healt…