Introduction

Before proceeding with the library and tutorials, it is recommended to familiarize yourself with some background theory behind SNNs, and the reasoning behind traceTorch. This isn’t strictly necessary, but understanding why certain things are done a certain way, as well as everything behind traceTorch should help you make and debug models.

Contents:

• 1. What is an SNN?
• 2. The Ethos of traceTorch
• 3. The traceTorch Layers
• 4. The Distributed Hidden State
• 5. Monotonic and Nonmonotonic Functions
• 6. Surrogate Derivatives