Visualization |

Instructor


Amaia Salvador (AS)

Zeiler, Matthew D., and Rob Fergus. “Visualizing and understanding convolutional networks.” In Computer vision–ECCV 2014, pp. 818-833. Springer International Publishing, 2014.
Yosinski, Jason, Jeff Clune, Anh Nguyen, Thomas Fuchs, and Hod Lipson. “Understanding neural networks through deep visualization.” International Conference on Machine Learning, ICML (2015).
Accepted papers at the ICML Visualization Workshop 2016.
Zintgraf, Luisa M., Taco S. Cohen, and Max Welling. “A new method to visualize deep neural networks.” arXiv preprint arXiv:1603.02518 (2016).
Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba. Learning Deep Features for Discriminative Localization, CVPR 2016. (Slides by Marc Bolaños)
Gregoire Montavon, Sebastian Bach, Alexander Binder, Wojciech Samek, Klaus-Robert Muller, “Deep Taylor Decomposition of Neural Networks”. ICML 2016 Visualization Workshop. [project page]
Jianming Zhang, Zhe Lin, Jonathan Brandt, Xiaohui Shen, Stan Sclaroff, “Top-down Neural Attention by Excitation Backprop”. ECCV 2016. [arxiv][code]
Antonio Torralba et al, DrawNet online demo.
Andrej Karpathy et al, ConvNetJS, deep learning in your browser.
Montavon, Grégoire, Sebastian Bach, Alexander Binder, Wojciech Samek, and Klaus-Robert Müller. “Explaining nonlinear classification decisions with deep taylor decomposition.” arXiv preprint arXiv:1512.02479 (2015). Demo
Quiver, Interactive deep convolutional networks features visualization. 2016.