Tutorials accessible in NengoGUI
The basics of how to build models and visualize them with NengoGUI are described in tutorials built into the NengoGUI. Access them through the built-in examples folder in the file view at the top-left.
basicsshows the basic features of NengoGUI in no particular order. Start here if you want a brief overview.
hbb_tutorialsis a set of tutorials from the book How to Build a Brain, updated to work with current versions of Nengo.
recurrentshows some dynamic neural networks like attractor networks that are straightforward to implement in Nengo.
tutorialis a set of 25 guided examples going from a network of one neuron to networks of hundreds of thousands of neurons implementing cognitive models.
- Coming from TensorFlow to NengoDL
- Coming from Nengo to NengoDL
- Classifying MNIST digits with a spiking neural network
- State of the art psMNIST results using Legendre Memory Units (LMUs)
- Other NengoDL examples
- Keyword spotting with NengoLoihi
- Nonlinear adaptive control with NengoLoihi
- CIFAR-10 classification convolutional network with NengoLoihi
- Other NengoLoihi examples
- Lorenz chaotic attractor with NengoFPGA
- MNIST classifier with NengoFPGA
- Adaptive pendulum control with NengoFPGA
- Reinforcement learning agent with NengFPGA
- Other NengoFPGA examples
- Supervised learning with the PES learning rule
- Supervised FORCE learning with the RLS learning rule
- Unsupervised association learning with the Voja learning rule
- Unsupervised synaptic plasticity rules
Neural Engineering Framework
- Summary of the NEF principles
- Nengo core examples
- Spiking MNIST with Gabor encoders
- Computing functions across a rolling window of time (LMU)