Entanglement-Embedded Recurrent Network Architecture: Tensorized Latent State Propagation and Chaos Forecasting

10 Jun 2020

Chaotic time series forecasting has been far less understood despite its tremendous potential in theory and real-world applications. Traditional statistical/ML methods are inefficient to capture chaos in nonlinear dynamical systems, especially when the time difference $\Delta t$ between consecutive steps is so large that a trivial, ergodic local minimum would most likely be reached instead... (read more)

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