Papers of Interest

Papers of Interest

For the evaluation of the theoretical aspects of the course, we offer a list of papers of interest which the student may chose to read and review. These are loosely are categorized. For older papers that have been thoroughly review by the community (> 2 years), the student will be expected to focus on novel interpretations of the contribution.

Convolutional Neural Networks

The next three papers should be read and reviewed together

Generative Adversarial Networks

Embedding spaces

The next four papers should be read and reviewed together

Multimodal Approaches

Transfer Learning

Recurrent Neural Networks

Theory of Deep Learning

High Performance Aspects of Deep Learning