In many natural and engineered systems, noise adds challenges for extracting effective dynamics from time series, at the same time it may have a constructive role of driving transitions between stable states. The authors propose a framework based on reservoir computing for learning noise-induced transitions from data.
- Zequn Lin
- Zhaofan Lu
- Ying Tang
