Noise & Order is an initiative to develop simple tools to explore the fundamentals of neural networks. We aim to understand the order within the noise, and how it can be harnessed to improve the performance of neural networks. We aim to develop tools that can be used to visualize and analyze the behavior of neural networks, and to understand how they learn and generalize.
Roadmap
TBD