PHY359H1

Understanding Neural Networks using Physics

Study of neural network architectures and algorithms from the perspective of physics, using both analytical and numerical tools. Topics will include classification and regression with fully-connected networks; physics-inspired optimizers and activation functions; generative models such as normalizing flows and diffusion models; residual networks and transformers.