71 citations · 106 across the 6 of their papers we have counts for
3 papers · 1 filter
Forecasting Sequential Data using Consistent Koopman Autoencoders
Omri Azencot, N. Benjamin Erichson, Vanessa Lin +1
Recurrent neural networks are widely used on time series data, yet such models often ignore the underlying physical structures in such sequences. A new class of physics-based metho…
Physics-informed Autoencoders for Lyapunov-stable Fluid Flow Prediction
N. Benjamin Erichson, Michael Muehlebach, Michael W. Mahoney
In addition to providing high-profile successes in computer vision and natural language processing, neural networks also provide an emerging set of techniques for scientific proble…
Shallow Neural Networks for Fluid Flow Reconstruction with Limited Sensors
N. Benjamin Erichson, Lionel Mathelin, Zhewei Yao +3
In many applications, it is important to reconstruct a fluid flow field, or some other high-dimensional state, from limited measurements and limited data. In this work, we propose…