Parallel circuit - a modular neural network architecture - Phan, Kien Tuong (2019)
One of the obstacles that hinder the development of Artificial Neural Networks (ANNs) is the heavy computational cost of the training process. In an attempt to address this problem, I proposed a lightweight model named Parallel Circuits (PCs), with an emphasis on modularity. One of the key inspirations for the proposed model is the human retina, which consists of various cell types that only respond to particular visual stimuli. Similarly, conventional ANNs with high redundancy are decomposed into semi-independent modules, which is deemed to provide more efficient learning, both in terms of speed and generalizability.