Tutorials

Learning-oriented, sequential guides. Work through them in order to go from a single-node simulation to building networks, mapping to signals, and fitting and training models with gradients. Each tutorial is a runnable Jupyter notebook.

For task-focused recipes see the How-To Guides; for the theory behind the models see Concepts.

• Your First Simulation
• Models and Dynamics
• Noise and Stochastic Runs
• Building a Network
• Forward Models
• Fitting with Gradients
• Gradient-Free Fitting
• Training on Tasks