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WIP most components now on Shadow DOM
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Ludwig Schubert
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@@ -7,7 +7,7 @@
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<d-front-matter>
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<script type="text/yml">
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title: Article Title
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title: Demo Title Attention and Augmented Recurrent Neural Networks
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published: Jan 10, 2017
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authors:
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- Chris Olah:
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@@ -19,10 +19,12 @@
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</d-front-matter>
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<d-article>
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<script type="text/article"></script>
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<h1>Hello World</h1>
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<h2>A description of the article</h2>
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<d-byline></d-byline>
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<d-title>
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<h1>Attention and Augmented Recurrent Neural Networks</h1>
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</d-title>
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<d-abstract>
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<p>This is the first paragraph of the article. Test a long — dash -- here it is.</p>
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</d-abstract>
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<p>This is the first paragraph of the article. Test a long — dash -- here it is.</p>
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<p>Test for owner's possessive. Test for "quoting a passage." And another sentence. Or two.</p>
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<p>Here's a test of an inline equation <d-math>c = a^2 + b^2</d-math>. And then there's a block equation:</p>
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@@ -30,7 +32,7 @@
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c = \pm \sqrt{ \sum_{i=0}^{n}{a^{222} + b^2}}
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</d-math>
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<p>We can also cite <d-cite key="gregor2015draw,mercier2011humans"></d-cite> external publications. <d-cite key="dong2014image,dumoulin2016guide,mordvintsev2015inceptionism"></d-cite></p>
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<p>We should also be testing footnotes<d-footnote>This will become a hoverable footnote.</d-footnote>.</p>
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<p>We should also be testing footnotes<d-footnote>This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote. This will become a hoverable footnote.</d-footnote>. There are multiple footnotes, and they appear in the appendix<d-footnote>Given I have coded them right. Also, here's math in a footnote: <d-math>c = \sum_0^i{x}<d-math>.</d-footnote> as well.</p>
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<table>
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<thead>
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<tr><th>First</th><th>Second</th><th>Third</th></tr>
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@@ -41,7 +43,7 @@
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<tr><td>234</td><td>54</td><td>23</td></tr>
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</tbody>
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</table>
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<h3>Displaying code snippets</h3>
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<h2>Displaying code snippets</h2>
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<p>Some inline javascript:<d-code language="javascript">var x = 25;</d-code></p>
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<p>Here's a javascript code block.</p>
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<d-code block language="javascript">
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@@ -59,114 +61,124 @@
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print(a, end=' ')
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a, b = b, a+b
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</d-code>
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<p>That's it for the example article!</p>
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</d-article>
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<d-bibliography>
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<script type="text/bibtex">
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<d-appendix>
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<d-acknowledgements>
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<h3>Contributions</h3>
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<p>Some text describing who did what.</p>
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<h4>Reviewers</h4>
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<p>Some text with links describing who reviewed the article.</p>
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</d-acknowledgements>
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@article{gregor2015draw,
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title={DRAW: A recurrent neural network for image generation},
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author={Gregor, Karol and Danihelka, Ivo and Graves, Alex and Rezende, Danilo Jimenez and Wierstra, Daan},
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journal={arXiv preprint arXiv:1502.04623},
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year={2015},
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url ={https://arxiv.org/pdf/1502.04623.pdf}
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}
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@article{mercier2011humans,
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title={Why do humans reason? Arguments for an argumentative theory},
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author={Mercier, Hugo and Sperber, Dan},
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journal={Behavioral and brain sciences},
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volume={34},
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number={02},
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pages={57--74},
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year={2011},
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publisher={Cambridge Univ Press},
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doi={10.1017/S0140525X10000968}
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}
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<d-footnote-list></d-footnote-list>
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@article{dong2014image,
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title={Image super-resolution using deep convolutional networks},
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author={Dong, Chao and Loy, Chen Change and He, Kaiming and Tang, Xiaoou},
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journal={arXiv preprint arXiv:1501.00092},
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year={2014},
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url={https://arxiv.org/pdf/1501.00092.pdf}
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}
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<d-bibliography>
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<script type="text/bibtex">
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@article{dumoulin2016adversarially,
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title={Adversarially Learned Inference},
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author={Dumoulin, Vincent and Belghazi, Ishmael and Poole, Ben and Lamb, Alex and Arjovsky, Martin and Mastropietro, Olivier and Courville, Aaron},
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journal={arXiv preprint arXiv:1606.00704},
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year={2016},
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url={https://arxiv.org/pdf/1606.00704.pdf}
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}
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@article{gregor2015draw,
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title={DRAW: A recurrent neural network for image generation},
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author={Gregor, Karol and Danihelka, Ivo and Graves, Alex and Rezende, Danilo Jimenez and Wierstra, Daan},
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journal={arXiv preprint arXiv:1502.04623},
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year={2015},
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url ={https://arxiv.org/pdf/1502.04623.pdf}
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}
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@article{mercier2011humans,
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title={Why do humans reason? Arguments for an argumentative theory},
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author={Mercier, Hugo and Sperber, Dan},
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journal={Behavioral and brain sciences},
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volume={34},
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number={02},
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pages={57--74},
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year={2011},
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publisher={Cambridge Univ Press},
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doi={10.1017/S0140525X10000968}
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}
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@article{dumoulin2016guide,
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title={A guide to convolution arithmetic for deep learning},
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author={Dumoulin, Vincent and Visin, Francesco},
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journal={arXiv preprint arXiv:1603.07285},
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year={2016},
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url={https://arxiv.org/pdf/1603.07285.pdf}
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}
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@article{dong2014image,
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title={Image super-resolution using deep convolutional networks},
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author={Dong, Chao and Loy, Chen Change and He, Kaiming and Tang, Xiaoou},
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journal={arXiv preprint arXiv:1501.00092},
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year={2014},
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url={https://arxiv.org/pdf/1501.00092.pdf}
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}
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@article{gauthier2014conditional,
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title={Conditional generative adversarial nets for convolutional face generation},
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author={Gauthier, Jon},
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journal={Class Project for Stanford CS231N: Convolutional Neural Networks for Visual Recognition, Winter semester},
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volume={2014},
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year={2014},
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url={http://www.foldl.me/uploads/papers/tr-cgans.pdf}
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}
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@article{dumoulin2016adversarially,
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title={Adversarially Learned Inference},
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author={Dumoulin, Vincent and Belghazi, Ishmael and Poole, Ben and Lamb, Alex and Arjovsky, Martin and Mastropietro, Olivier and Courville, Aaron},
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journal={arXiv preprint arXiv:1606.00704},
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year={2016},
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url={https://arxiv.org/pdf/1606.00704.pdf}
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}
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@article{johnson2016perceptual,
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title={Perceptual losses for real-time style transfer and super-resolution},
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author={Johnson, Justin and Alahi, Alexandre and Fei-Fei, Li},
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journal={arXiv preprint arXiv:1603.08155},
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year={2016},
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url={https://arxiv.org/pdf/1603.08155.pdf}
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}
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@article{dumoulin2016guide,
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title={A guide to convolution arithmetic for deep learning},
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author={Dumoulin, Vincent and Visin, Francesco},
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journal={arXiv preprint arXiv:1603.07285},
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year={2016},
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url={https://arxiv.org/pdf/1603.07285.pdf}
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}
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@article{mordvintsev2015inceptionism,
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title={Inceptionism: Going deeper into neural networks},
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author={Mordvintsev, Alexander and Olah, Christopher and Tyka, Mike},
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journal={Google Research Blog},
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year={2015},
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url={https://research.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html}
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}
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@article{gauthier2014conditional,
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title={Conditional generative adversarial nets for convolutional face generation},
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author={Gauthier, Jon},
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journal={Class Project for Stanford CS231N: Convolutional Neural Networks for Visual Recognition, Winter semester},
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volume={2014},
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year={2014},
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url={http://www.foldl.me/uploads/papers/tr-cgans.pdf}
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}
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@misc{mordvintsev2016deepdreaming,
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title={DeepDreaming with TensorFlow},
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author={Mordvintsev, Alexander},
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year={2016},
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url={https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/deepdream/deepdream.ipynb},
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}
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@article{johnson2016perceptual,
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title={Perceptual losses for real-time style transfer and super-resolution},
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author={Johnson, Justin and Alahi, Alexandre and Fei-Fei, Li},
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journal={arXiv preprint arXiv:1603.08155},
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year={2016},
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url={https://arxiv.org/pdf/1603.08155.pdf}
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}
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@article{radford2015unsupervised,
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title={Unsupervised representation learning with deep convolutional generative adversarial networks},
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author={Radford, Alec and Metz, Luke and Chintala, Soumith},
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journal={arXiv preprint arXiv:1511.06434},
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year={2015},
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url={https://arxiv.org/pdf/1511.06434.pdf}
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}
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@article{mordvintsev2015inceptionism,
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title={Inceptionism: Going deeper into neural networks},
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author={Mordvintsev, Alexander and Olah, Christopher and Tyka, Mike},
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journal={Google Research Blog},
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year={2015},
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url={https://research.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html}
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}
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@inproceedings{salimans2016improved,
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title={Improved techniques for training gans},
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author={Salimans, Tim and Goodfellow, Ian and Zaremba, Wojciech and Cheung, Vicki and Radford, Alec and Chen, Xi},
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booktitle={Advances in Neural Information Processing Systems},
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pages={2226--2234},
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year={2016},
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url={https://arxiv.org/pdf/1606.03498.pdf}
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}
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@misc{mordvintsev2016deepdreaming,
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title={DeepDreaming with TensorFlow},
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author={Mordvintsev, Alexander},
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year={2016},
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url={https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/deepdream/deepdream.ipynb},
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}
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@article{shi2016deconvolution,
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title={Is the deconvolution layer the same as a convolutional layer?},
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author={Shi, Wenzhe and Caballero, Jose and Theis, Lucas and Huszar, Ferenc and Aitken, Andrew and Ledig, Christian and Wang, Zehan},
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journal={arXiv preprint arXiv:1609.07009},
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year={2016},
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url={https://arxiv.org/pdf/1609.07009.pdf}
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}
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@article{radford2015unsupervised,
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title={Unsupervised representation learning with deep convolutional generative adversarial networks},
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author={Radford, Alec and Metz, Luke and Chintala, Soumith},
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journal={arXiv preprint arXiv:1511.06434},
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year={2015},
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url={https://arxiv.org/pdf/1511.06434.pdf}
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}
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@inproceedings{salimans2016improved,
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title={Improved techniques for training gans},
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author={Salimans, Tim and Goodfellow, Ian and Zaremba, Wojciech and Cheung, Vicki and Radford, Alec and Chen, Xi},
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booktitle={Advances in Neural Information Processing Systems},
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pages={2226--2234},
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year={2016},
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url={https://arxiv.org/pdf/1606.03498.pdf}
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}
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@article{shi2016deconvolution,
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title={Is the deconvolution layer the same as a convolutional layer?},
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author={Shi, Wenzhe and Caballero, Jose and Theis, Lucas and Huszar, Ferenc and Aitken, Andrew and Ledig, Christian and Wang, Zehan},
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journal={arXiv preprint arXiv:1609.07009},
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year={2016},
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url={https://arxiv.org/pdf/1609.07009.pdf}
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}
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</script>
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</d-bibliography>
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<d-appendix>
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<h3>Contributions</h3>
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<p>List of who did what</p>
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<distill-appendix> </distill-appendix>
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</d-appendix>
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