Unveiling the Crystal Structure of Neural Networks: A New Perspective on ReLU's Power

This article offers a fascinating deep dive into the internal workings of ReLU networks, revealing their topology as a series of interconnected, crystal-like structures. It provides a novel way to understand how these networks process data, moving beyond the traditional view of them as smooth function approximators. The visualizations and code offer a valuable tool for researchers and enthusiasts alike.

• •ReLU networks divide input space into crystal-like polyhedra.
• •Each point in the input space gets a 'digital address' based on neuron activation.
• •The article provides code and visualizations to make complex concepts intuitive.