Add contribution section

Made ####, since ### stands out too much.

Author: hunkim

README.md

@@ -1,65 +1,68 @@
 # Tensorflow implementations
 
-### Very simple TensorFlow Examples
+#### Very simple TensorFlow examples
 * Code: https://github.com/nlintz/TensorFlow-Tutorials
 
-### Sequence to Sequence -- Video to Text
+#### Sequence to Sequence -- Video to Text
 * Subhashini Venugopalan, Marcus Rohrbach, Jeff Donahue, Raymond Mooney, Trevor Darrell, Kate Saenko, arxiv, 2015
 * [[code](https://github.com/jazzsaxmafia/video_to_sequence)]
 * [[paper](http://arxiv.org/pdf/1505.00487v3.pdf)]
 
-### Sequence to Sequence -- chatbot
+#### Sequence to Sequence -- chatbot
 * Oriol Vinyals, Quoc V. Le, arxiv, 2015
 * [[code](https://github.com/nicolas-ivanov/tf_seq2seq_chatbot)]
 * [[paper](http://arxiv.org/pdf/1506.05869v1.pdf)]
 
-### Show and Tell: A Neural Image Caption Generator
+#### Show and Tell: A Neural Image Caption Generator
 * Oriol Vinyals, Alexander Toshev, Samy Bengio, Dumitru Erhan, arxiv, 2015
 * [[code](https://github.com/jazzsaxmafia/show_and_tell.tensorflow)]
 * [[paper](http://arxiv.org/pdf/1411.4555v2.pdf)]
 
-### Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
+#### Show, Attend and Tell: Neural Image Caption Generation with Visual Attention
 * Kelvin Xu, Jimmy Ba, Ryan Kiros, Kyunghyun Cho, Aaron Courville, Ruslan Salakhutdinov, Richard Zemel, Yoshua Bengio, ICLR, 2014
 * [[code](https://github.com/jazzsaxmafia/show_attend_and_tell.tensorflow)]
 * [[paper](http://arxiv.org/pdf/1502.03044.pdf)]
 
-### Learning Deep Features for Discriminative Localization
+#### Learning Deep Features for Discriminative Localization
 * Bolei Zhou, Aditya Khosla, Agata Lapedriza, Aude Oliva, Antonio Torralba, CVPR, 2016
 * [[code](https://github.com/jazzsaxmafia/Weakly_detector)]
 * [[paper](http://arxiv.org/pdf/1512.04150v1.pdf)]
 
-### Deep Visual Analogy-Making
+#### Deep Visual Analogy-Making
 * Scott Reed, Yi Zhang, Yuting Zhang, Honglak Lee, NIPS, 2015
 * [[code](https://github.com/carpedm20/visual-analogy-tensorflow)]
 * [[paper](http://www-personal.umich.edu/~reedscot/nips2015.pdf)]
 
-### Deep Convolutional Generative Adversarial Networks 
+#### Deep Convolutional Generative Adversarial Networks 
 * Alec Radford, Luke Metz, Soumith Chintala, arxiv, 2015
 * [[code](https://github.com/carpedm20/DCGAN-tensorflow)]
 * [[paper](http://arxiv.org/pdf/1511.06434v2.pdf)]
 
-### End-To-End Memory Networks
+#### End-To-End Memory Networks
 * Sainbayar Sukhbaatar, Arthur Szlam, Jason Weston, Rob Fergus, NIPS, 2015
 * [[code](https://github.com/carpedm20/MemN2N-tensorflow)]
 * [[paper](http://arxiv.org/pdf/1503.08895v4.pdf)]
 
-### Character-Aware Neural Language Models
+#### Character-Aware Neural Language Models
 * Yoon Kim, Yacine Jernite, David Sontag, Alexander M. Rush, AAAI, 2016
 * [[code](https://github.com/carpedm20/lstm-char-cnn-tensorflow)]
 * [[paper](http://arxiv.org/pdf/1508.06615v4.pdf)]
 
-### Deep Reinforcement Learning
+#### Deep Reinforcement Learning
 * Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin Riedmiller, NIPS, 2013
 * [[code](https://github.com/nivwusquorum/tensorflow-deepq)]
 * [[paper](http://arxiv.org/abs/1312.5602)]
 
-### Using Deep Q-Network to Learn How To Play Flappy Bird
+#### Using Deep Q-Network to Learn How To Play Flappy Bird
 * Kevin Chen, Deep Reinforcement Learning for Flappy Bird, Report from http://cs229.stanford.edu/ 2015 project
 * [[code](https://github.com/DeepLearningProjects/DeepLearningFlappyBird)]
 * [[report](http://cs229.stanford.edu/proj2015/362_report.pdf)]
 
-### Semi-Supervised Learning with Ladder Network 
+#### Semi-Supervised Learning with Ladder Network 
  *  A Rasmus, H Valpola, M Honkala, M Berglund, and T Raiko, NIPS, 2015
  * [[code](https://github.com/rinuboney/ladder)]
  * [[paper](https://papers.nips.cc/paper/5947-semi-supervised-learning-with-ladder-networks.pdf)]
  * [[Additional Material](http://rinuboney.github.io/2016/01/19/ladder-network.html)]
+
+## Contribution
+Did you find new TensorFlow implementations? Pull requests are always welcome.