Continuous Thought Machines
Models
This folder contains all model-related code.
Some notes for clarity:
- The resnet structure we used (see resnet.py) has a few minor changes that enable constraining the receptive field of the features yielded. We do this because we want the CTM (or baseline methods) to learn a process whereby they gather information. Neural networks that use SGD will find the path of least resistence, even if that path doesn't result in actually intelligent behaviour. Constraining the receptive field helps to prevent this, a bit.