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