README.md

Network architectures

Three main architectures are currently available:

PrednetModel.py: implementation of PredNet in PyTorch through the following smaller blocks:
- DiscriminativeCell.py: computes the error between the input and state projections;
- GenerativeCell.py: computes the new state given error, top down state, and current state. Uses the following custom module:
  - ConvLSTMCell.py: a pretty standard LSTM that uses convolutions instead of FC layers;
Model01.py: symmetric, additional feed-forward/back;
Model02.py: AKA CortexNet, additional feed-forward, modulated feed-back. May use:
- RG.py: recurrent generative block ⇒ Model02G.