<commit_before>---
layout: page
title: Visualization
permalink: /visualization
hide: true
---

## Instructor

| ![AmaiaSalvador][AmaiaSalvador-photo]  |
|:-:|:-:|:-:|:-:|:-:|:-:|
| [<NAME> (AS)][AmaiaSalvador-web] |

[AmaiaSalvador-web]: https://imatge.upc.edu/web/people/amaia-salvador

[AmaiaSalvador-photo]: img/instructors/AmaiaSalvador.jpg "<NAME>"

## Slides
[Slides](slides/D2L3-visualization.pdf)

## Related Work & Resources

* Zeiler, <NAME>., and <NAME>. ["Visualizing and understanding convolutional networks."](http://arxiv.org/abs/1311.2901) In Computer vision–ECCV 2014, pp. 818-833. Springer International Publishing, 2014.

* Yosinski, Jason, <NAME>, <NAME>, <NAME>, and <NAME>. ["Understanding neural networks through deep visualization."](http://yosinski.com/deepvis) International Conference on Machine Learning, ICML (2015).

* [Accepted papers](http://icmlviz.github.io/papers/) at the ICML Visualization Workshop 2016.

* Zintgraf, <NAME>., <NAME>, and <NAME>. ["A new method to visualize deep neural networks."](http://arxiv.org/abs/1603.02518) arXiv preprint arXiv:1603.02518 (2016).

* <NAME>, <NAME>, <NAME>, <NAME>, <NAME>. [Learning Deep Features for Discriminative Localization](http://cnnlocalization.csail.mit.edu/">Learning Deep Features for Discriminative Localization), CVPR 2016. ([Slides by Marc Bolaños](https://docs.google.com/presentation/d/1CItqjtAYa_OKVLs5BqqCzM8dEbCwkwit4Ooem_WJpY0/edit#slide=id.p))

* <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, ["Top-down Neural Attention by Excitation Backprop"](https://arxiv.org/abs/1608.00507). ECCV 2016.

* Antonio Torralba et al, [DrawNet online demo](http://people.csail.mit.edu/torralba/research/drawCNN/drawNet.html).

* <NAME> et al, [ConvNetJS, deep learning in your browser](http://cs.stanford.edu/people/karpathy/convnetjs/).

*  Montavon, Grégoire, <NAME>, <NAME>, <NAME>, and <NAME>. "Explaining nonlinear classification decisions with deep taylor decomposition." arXiv preprint arXiv:1512.02479 (2015). [Demo](http://www.heatmapping.org/deeptaylor/tutorial/index.html)<commit_msg>Link to github for Top-down Neural Attention<commit_after>---
layout: page
title: Visualization
permalink: /visualization
hide: true
---

## Instructor

| ![AmaiaSalvador][AmaiaSalvador-photo]  |
|:-:|:-:|:-:|:-:|:-:|:-:|
| [Amaia Salvador (AS)][AmaiaSalvador-web] |

[AmaiaSalvador-web]: https://imatge.upc.edu/web/people/amaia-salvador

[AmaiaSalvador-photo]: img/instructors/AmaiaSalvador.jpg "Amaia Salvador"

## Slides
[Slides](slides/D2L3-visualization.pdf)

## Related Work & Resources

* Zeiler, <NAME>., and <NAME>ergus. ["Visualizing and understanding convolutional networks."](http://arxiv.org/abs/1311.2901) In Computer vision–ECCV 2014, pp. 818-833. Springer International Publishing, 2014.

* Yosinski, Jason, <NAME>, <NAME>, <NAME>, and <NAME>. ["Understanding neural networks through deep visualization."](http://yosinski.com/deepvis) International Conference on Machine Learning, ICML (2015).

* [Accepted papers](http://icmlviz.github.io/papers/) at the ICML Visualization Workshop 2016.

* Zintgraf, <NAME>., <NAME>, and <NAME>. ["A new method to visualize deep neural networks."](http://arxiv.org/abs/1603.02518) arXiv preprint arXiv:1603.02518 (2016).

* <NAME>, <NAME>, <NAME>, <NAME>, <NAME>. [Learning Deep Features for Discriminative Localization](http://cnnlocalization.csail.mit.edu/">Learning Deep Features for Discriminative Localization), CVPR 2016. ([Slides by Marc Bolaños](https://docs.google.com/presentation/d/1CItqjtAYa_OKVLs5BqqCzM8dEbCwkwit4Ooem_WJpY0/edit#slide=id.p))

* <NAME>, <NAME>, <NAME>, <NAME>, <NAME>, ["Top-down Neural Attention by Excitation Backprop"](https://arxiv.org/abs/1608.00507). ECCV 2016. [[project](https://github.com/jimmie33/Caffe-ExcitationBP)]

* <NAME>ba et al, [DrawNet online demo](http://people.csail.mit.edu/torralba/research/drawCNN/drawNet.html).

* <NAME> et al, [ConvNetJS, deep learning in your browser](http://cs.stanford.edu/people/karpathy/convnetjs/).

*  Montavon, Grégoire, <NAME>, <NAME>, <NAME>, and <NAME>. "Explaining nonlinear classification decisions with deep taylor decomposition." arXiv preprint arXiv:1512.02479 (2015). [Demo](http://www.heatmapping.org/deeptaylor/tutorial/index.html)
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