Omri Barak

We present a neural network-based method using Koopman Eigenfunctions to efficiently identify separatrices in high-dimensional dynamical systems, validated on synthetic, ecological, and neural network models.

We develop a mathematical theory of closed-loop learning in RNNs, showing how it fundamentally differs from conventional open-loop supervise training.