Detecting systematic structure in distributed representations.
A novel method of analysing the systematic structure formed inside a feedforward neural network is developed. This method is applied to the task of understanding how a network is performing unification on distributed representations. Systematic structure is detected by examining inter-representational distances, rather than by attempting to detect the vectorial similarities sought by previously described techniques. The method described can be applied to the detection of systematic structure in other networks using distributed representations.
Browne
Antony
A
School of Information Systems, University College Northampton, Northampton, UK