A Brief Tour of Deep Learning from a Statistical Perspective
Eric Nalisnick, Padhraic Smyth, Dustin Tran · Annual Review of Statistics and Its Application · 2023
We expose the statistical foundations of deep learning with the goal of facilitating conversation between the deep learning and statistics communities. We highlight core themes at the intersection; summarize key neural models, such as feedforward neural networks, sequential neural networks, and neural latent variable models; and link these ideas to their roots in probability and statistics. We also highlight research directions in deep learning where there are opportunities for statistical contributions.