Understanding Learning Dynamics of Neural Networks

This lecture delves into the learning dynamics of neural networks, exploring topics such as optimization, interference during learning, and continual learning. It discusses the challenges of credit assignment, plasticity, and the efficiency of linear recurrences. The instructor presents insights on preventing exploding and vanishing gradients, the benefits of linear recurrences, and the efficiency of different models in various tasks.