In this talk, we shall cover three main topics:
- the concept of automatic differentiation and it’s types of implementation
o the tools that implement automatic differentiation of various forms
- PyTorch as one such tool, including it’s coverage of gradient-based learning methods and neural networks
- Graph Neural Networks and their recent coverage
o Implementing Graph Neural Networks in PyTorch