1. [ ] BrainNetCNN: Convolutional neural networks for brain networks; towards predicting neurodevelopment \cite{Kawahara2017}

Representation Learning

  1. [ ] Representation Learning for Cross-Modality Classification \cite{van_Tulder_2017}

Reinforcement Learning

  1. [ ] Mastering Chess and Shogi by Self-Play with a General Reinforcement Learning Algorithm \cite{1712.01815}

Deep Networks Visualisation and Interpretation

  1. [x] CNN Fixations: An unraveling approach to visualize the discriminative image regions \cite{Mopuri2017}
  2. [x] Visualizing Deep Neural Network Decisions: Prediction Difference Analysis \cite{Zintgraf2017}
  3. [x] Soft Proposal Networks for Weakly Supervised Object Localization \cite{Zhu2017}
  4. [ ] The (Un)reliability of saliency methods \cite{kindermans2017reliability}
  5. [ ] DeepXplore: Automated Whitebox Testing of Deep Learning Systems \cite{pei2017deepxplore}
  6. [ ] Feature Visualisation \cite{olah2017feature}  (new blog from google with fancy images)
  7. [ ] This is the 'book' I mentioned on 07/12/2017: https://christophm.github.io/interpretable-ml-book/