Norse Notebook Tutorials

These notebooks are designed to familiarize yourself with the Spiking Neural Network simulator, Norse. These notebooks can be directly run in your browser. However, please note that the online execution relies on CPU, which can cause performance problems for larger networks. If you desire hardware acceleration (like GPU or TPU) you can either clone this repository and experiment locally, or use Google Colab.

If this is your first brush with computational neuroscience, we recommend this excellent serious of tutorials by Neuromatch Academy. They provide excellent interactive tutorials on neuron dynamics, linear algebra, calculus, statistics, and deep learning.

Introductory notebooks

Create

Notebook	Topic
Introduction to PyTorch and spiking neurons	Introduces biological neurons and PyTorch
Introduction to Spiking Neural Networks in Norse	Build and train spiking models in Norse
Simulating and plotting spiking data	Learn how to describe and visualise event data

Supervised Learning

Notebook	Topic
Training with MNIST	Learn how to solve MNIST with spikes
Learning event-based DVS Poker	Learn how to work with event-based datasets by classifying a set of poker cards

Real-time event processing

Notebook	Topic
Edge detection with Norse	Process events from .aedat4 files with Norse. Prerequisite to streaming real-time events.

Neuroscience

Notebook	Topic
Optimizing neuron parameters	Learn how to solve MNIST with spikes
Spike time dependent plasticity	Learn how to work with event-based datasets by classifying a set of poker cards

Miscellaneous

Notebook	Topic
High Performance Computing with Norse	Scale Norse models to HPCs!
Stochastic Computing	Explore stochastic computing with spiking neurons

For more information we refer to our documentation.

We are also more than happy to accept contributions such as improving or adding notebooks, suggestions for improvements, issues for bugs, or donations to support our work. Thank you!