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Found 3 papers, 1 papers with code
Lyapunov-Guided Representation of Recurrent Neural Network Performance
To address the fact that RNN features go beyond the existing Lyapunov spectral analysis, we propose to infer relevant features from the Lyapunov spectrum with an Autoencoder and an embedding of its latent representation (AeLLE).
Quantum Physics without the Physics
This report explains the basic theory and common terminology of quantum physics without assuming any knowledge of physics.
Quantum Physics Mathematical Physics Mathematical Physics 65-00, 81-00
On Lyapunov Exponents for RNNs: Understanding Information Propagation Using Dynamical Systems Tools
Recurrent neural networks (RNNs) have been successfully applied to a variety of problems involving sequential data, but their optimization is sensitive to parameter initialization, architecture, and optimizer hyperparameters.
