lychrel / CMLnn

Learning to use spatiotemporal chaos

cmlnn

Learning to use spatiotemporal chaos

Basic idea

Coupled map lattices (CMLs) exhibit robust nonlinear functional capacity with few parameters. As such they might prove a useful computational tool for deep neural networks. Currently this is just a first-pass notebook.

Errata

• This is in Keras but must move to PyTorch:
  • I need layerwise learning rates so that dynamics can be learned slower than initialization, which Keras doesn't yet support
• Learning requires a slight modification of CML update:
  • the lattice boundaries must update independently instead of referencing neighbors.
    • visually, dynamics seem unaffected by this, but should validate further