Schedule

March 17:

• paper: https://arxiv.org/pdf/1512.03385.pdf
• slides: http://icml.cc/2016/tutorials/icml2016_tutorial_deep_residual_networks_kaiminghe.pdf
• presenter: Sumedha

March 24, 31:

We will go over the CNN chapter of the book and then read a research paper that uses CNNs with dilated convolutions to account for contextual information:

March 24

• tutorial: http://www.deeplearningbook.org/contents/convnets.html
• presenter: Chakra

March 31

• tutorial: quick overview of CNNs as relevant to paper
• research: https://arxiv.org/pdf/1511.07122.pdf
• presenter: ??

April 7: Evaluating learned representations

• research: https://arxiv.org/pdf/1509.06321.pdf
• optional: http://journals.plos.org/plosone/article?id=10.1371/journal.pone.0130140#sec002
• presenter: David Koes

April 14, 21

• Tutorial: http://www.deeplearningbook.org/contents/optimization.html
• research: TBD

April 28, May 5, 12, 19:

• Tutorial: https://www.coursera.org/learn/probabilistic-graphical-models
• Presenter : Fattaneh
• Research: TBD (perhaps GAN paper)