1 code implementation • 9 Nov 2022 • Alexander Wikner, Joseph Harvey, Michelle Girvan, Brian R. Hunt, Andrew Pomerance, Thomas Antonsen, Edward Ott
In this article, we systematically examine the technique of adding noise to the ML model input during training to promote stability and improve prediction accuracy.
no code implementations • 15 Feb 2021 • Alexander Wikner, Jaideep Pathak, Brian R. Hunt, Istvan Szunyogh, Michelle Girvan, Edward Ott
We show that by using partial measurements of the state of the dynamical system, we can train a machine learning model to improve predictions made by an imperfect knowledge-based model.
1 code implementation • 9 Oct 2019 • Pantelis R. Vlachas, Jaideep Pathak, Brian R. Hunt, Themistoklis P. Sapsis, Michelle Girvan, Edward Ott, Petros Koumoutsakos
We examine the efficiency of Recurrent Neural Networks in forecasting the spatiotemporal dynamics of high dimensional and reduced order complex systems using Reservoir Computing (RC) and Backpropagation through time (BPTT) for gated network architectures.
no code implementations • 19 Oct 2017 • Jaideep Pathak, Zhixin Lu, Brian R. Hunt, Michelle Girvan, Edward Ott
For the case of the KS equation, we note that as the system's spatial size is increased, the number of Lyapunov exponents increases, thus yielding a challenging test of our method, which we find the method successfully passes.
Chaotic Dynamics