Matrix Neural Networks

Understand

Traditional neural networks assume vectorial inputs as the network is arranged as layers of single line of computing units called neurons.

• This special structure requires the non-vectorial inputs such as matrices to be converted into vectors.
• This process can be problematic.
• Firstly, the spatial information among elements of the data may be lost during vectorisation.