project-krmiddlebrook/article-no-citations.html at gh-pages · krmiddlebrook/project-krmiddlebrook · GitHub

1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
<!--
  Copyright 2018 The Distill Template Authors

  Licensed under the Apache License, Version 2.0 (the "License");
  you may not use this file except in compliance with the License.
  You may obtain a copy of the License at

       http://www.apache.org/licenses/LICENSE-2.0

  Unless required by applicable law or agreed to in writing, software
  distributed under the License is distributed on an "AS IS" BASIS,
  WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
  See the License for the specific language governing permissions and
  limitations under the License.
-->
<!doctype html>

<head>
  <meta charset="utf8">

  <script src="../dist/components.js"></script>

  <d-front-matter>
    <script type="text/yml">
      title: Demo Title Attention and Augmented Recurrent Neural Networks
      published: Jan 10, 2017
      authors:
      - Chris Olah:
      - Shan Carter: http://shancarter.com
      affiliations:
      - Google Brain
      - Google Brain: http://g.co/brain
    </script>
  </d-front-matter>
</head>

<body>
<d-article>
  <d-title>
    <h1>Attention and Augmented Recurrent Neural Networks</h1>
    <!-- <h2>Some people want a deck</h2> -->
    <d-byline></d-byline>
  </d-title>
  <d-abstract>
    <p>This is the first paragraph of the article. Test a long&thinsp;&mdash;&thinsp;dash -- here it is.</p>
  </d-abstract>
  <p>This is the first paragraph of the article. Test a long&thinsp;&mdash;&thinsp;dash -- here it is.</p>
  <p>Test for owner's possessive. Test for "quoting a passage." And another sentence. Or two. Some flopping fins; for diving.</p>
  <hr>
  <div style="max-width: 800px; background-color: red; height: 100px; border-radius: 50px;"></div>
  <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>
  <d-math block>
      c = \pm \sqrt{ \sum_{i=0}^{n}{a^{222} + b^2}}
  </d-math>
  <table>
    <thead>
      <tr><th>First</th><th>Second</th><th>Third</th></tr>
    </thead>
    <tbody>
      <tr><td>23</td><td>654</td><td>23</td></tr>
      <tr><td>14</td><td>54</td><td>34</td></tr>
      <tr><td>234</td><td>54</td><td>23</td></tr>
    </tbody>
  </table>
  <h2>Displaying code snippets</h2>
  <p>Some inline javascript:<d-code language="javascript">var x = 25;</d-code></p>
  <p>Here's a javascript code block.</p>
  <d-code block language="javascript">
      var x = 25;
      function(x){
        return x * x;
      }
  </d-code>
  <p>We also support python.</p>
  <d-code block language="python">
    # Python 3: Fibonacci series up to n
    def fib(n):
      a, b = 0, 1
        while a < n:
          print(a, end=' ')
          a, b = b, a+b
  </d-code>
  <p>That's it for the example article!</p>
  <aside>Some text.</aside>
</d-article>

<d-appendix>
  <d-acknowledgements>
    <h3>Contributions</h3>
    <p>Some text describing who did what.</p>
    <h4>Reviewers</h4>
    <p>Some text with links describing who reviewed the article.</p>
  </d-acknowledgements>

  <d-footnote-list></d-footnote-list>

  <d-bibliography><script type="text/bibtex">

      @article{gregor2015draw,
        title={DRAW: A recurrent neural network for image generation},
        author={Gregor, Karol and Danihelka, Ivo and Graves, Alex and Rezende, Danilo Jimenez and Wierstra, Daan},
        journal={arXiv preprint arXiv:1502.04623},
        year={2015},
        url ={https://arxiv.org/pdf/1502.04623.pdf}
      }
      @article{mercier2011humans,
        title={Why do humans reason? Arguments for an argumentative theory},
        author={Mercier, Hugo and Sperber, Dan},
        journal={Behavioral and brain sciences},
        volume={34},
        number={02},
        pages={57--74},
        year={2011},
        publisher={Cambridge Univ Press},
        doi={10.1017/S0140525X10000968}
      }

      @article{dong2014image,
        title={Image super-resolution using deep convolutional networks},
        author={Dong, Chao and Loy, Chen Change and He, Kaiming and Tang, Xiaoou},
        journal={arXiv preprint arXiv:1501.00092},
        year={2014},
        url={https://arxiv.org/pdf/1501.00092.pdf}
      }

      @article{dumoulin2016adversarially,
        title={Adversarially Learned Inference},
        author={Dumoulin, Vincent and Belghazi, Ishmael and Poole, Ben and Lamb, Alex and Arjovsky, Martin and Mastropietro, Olivier and Courville, Aaron},
        journal={arXiv preprint arXiv:1606.00704},
        year={2016},
        url={https://arxiv.org/pdf/1606.00704.pdf}
      }

      @article{dumoulin2016guide,
        title={A guide to convolution arithmetic for deep learning},
        author={Dumoulin, Vincent and Visin, Francesco},
        journal={arXiv preprint arXiv:1603.07285},
        year={2016},
        url={https://arxiv.org/pdf/1603.07285.pdf}
      }

      @article{gauthier2014conditional,
        title={Conditional generative adversarial nets for convolutional face generation},
        author={Gauthier, Jon},
        journal={Class Project for Stanford CS231N: Convolutional Neural Networks for Visual Recognition, Winter semester},
        volume={2014},
        year={2014},
        url={http://www.foldl.me/uploads/papers/tr-cgans.pdf}
      }

      @article{johnson2016perceptual,
        title={Perceptual losses for real-time style transfer and super-resolution},
        author={Johnson, Justin and Alahi, Alexandre and Fei-Fei, Li},
        journal={arXiv preprint arXiv:1603.08155},
        year={2016},
        url={https://arxiv.org/pdf/1603.08155.pdf}
      }

      @article{mordvintsev2015inceptionism,
        title={Inceptionism: Going deeper into neural networks},
        author={Mordvintsev, Alexander and Olah, Christopher and Tyka, Mike},
        journal={Google Research Blog},
        year={2015},
        url={https://research.googleblog.com/2015/06/inceptionism-going-deeper-into-neural.html}
      }

      @misc{mordvintsev2016deepdreaming,
        title={DeepDreaming with TensorFlow},
        author={Mordvintsev, Alexander},
        year={2016},
        url={https://github.com/tensorflow/tensorflow/blob/master/tensorflow/examples/tutorials/deepdream/deepdream.ipynb},
      }

      @article{radford2015unsupervised,
        title={Unsupervised representation learning with deep convolutional generative adversarial networks},
        author={Radford, Alec and Metz, Luke and Chintala, Soumith},
        journal={arXiv preprint arXiv:1511.06434},
        year={2015},
        url={https://arxiv.org/pdf/1511.06434.pdf}
      }

      @inproceedings{salimans2016improved,
        title={Improved techniques for training gans},
        author={Salimans, Tim and Goodfellow, Ian and Zaremba, Wojciech and Cheung, Vicki and Radford, Alec and Chen, Xi},
        booktitle={Advances in Neural Information Processing Systems},
        pages={2226--2234},
        year={2016},
        url={https://arxiv.org/pdf/1606.03498.pdf}
      }

      @article{shi2016deconvolution,
        title={Is the deconvolution layer the same as a convolutional layer?},
        author={Shi, Wenzhe and Caballero, Jose and Theis, Lucas and Huszar, Ferenc and Aitken, Andrew and Ledig, Christian and Wang, Zehan},
        journal={arXiv preprint arXiv:1609.07009},
        year={2016},
        url={https://arxiv.org/pdf/1609.07009.pdf}
      }

    </script></d-bibliography>

  <distill-appendix> </distill-appendix>
</d-appendix>
</body>