This session consists of two parts: a whirlwind introduction to PyTorch and its use in neuromorphics.

The first part (20 minutes) will explain the fundamentals of PyTorch by

• How PyTorch works with tensors and network layers
• How PyTorch propagates gradients
• How PyTorch can optimize networks

The second part (30 minutes) will explain how we can use PyTorch in neuromorphics by

• Introducing spiking simulations via the PyTorch extension Norse (github.com/norse/norse)
• Connecting to event cameras with AEStream (github.com/aestream/aestream)
• Real-time edge detection of event data with an SNN