DL 6890 Deep Learning
Paper Presentations

  1. Deep Reinforcement Learning:
  2. Combining Sequence Models with Reinforcement Learning:
  3. Image Segmentation and Generation: Upsampling through Transposed Convolution and Max Unpooling:
  4. Generative Adversarial Networks (GAN):
  5. Deep Networks and Generalization:
  6. Adversarial Examples: Part 1 and Part 2:
  7. Memory Augmented Networks:
  8. Capsule Networks:
  9. Deep Learning and Newtonian Physics:
  10. Combining Deep Learning with Conditional Random Fields:
  11. Semantic Parsing with Sequence-to-Sequence Models: