Best Awesome List: Deep Learning Foundation Resources

The highest-signal resources on Awesome List: Deep Learning Foundation, ranked by community reviews and momentum.
Canonical intent: topic=al-deep-learning-foundation|type=all|year=evergreen

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Top Picks

1

Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) | Attendemia

Unknown author

F4e3acdd b497 4a5d b512 1d3f5041b930Nov 23, 2015·9987 checkouts·attendemia.com

2

Deformable Convolutional Networks

Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, Yichen Wei

885d4d0e 49c4 4573 b198 829456263145Mar 22, 2017·9895 checkouts·arxiv.org

3

Understanding Neural Networks Through Deep Visualization

Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, Hod Lipson

F320f54a 3f05 4589 933e 37a0d4333505Jun 22, 2015·9801 checkouts·arxiv.org

4

Wasserstein GAN

Martin Arjovsky, Soumith Chintala, Léon Bottou

5975eb63 6cad 40ae 8cca 025f002df284Jan 26, 2017·9773 checkouts·arxiv.org

5

Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models

Sergey Ioffe

677166cc 5d27 4b10 8779 b40e91e8a318Mar 30, 2017·9737 checkouts·arxiv.org

6

Weakly Supervised Object Localization with Multi-fold Multiple Instance Learning

Ramazan Gokberk Cinbis, Jakob Verbeek, Cordelia Schmid

Abfc9399 e382 4765 b7b1 faf895c0fb78Feb 22, 2016·9718 checkouts·arxiv.org

7

Convolutional Neural Networks for Sentence Classification

Yoon Kim

23ed26c3 b1a1 4ece acdf 420a04bdb98eSep 3, 2014·9707 checkouts·arxiv.org

8

Ask Me Anything: Dynamic Memory Networks for Natural Language Processing

Ankit Kumar, Ozan Irsoy, Peter Ondruska, Mohit Iyyer, James Bradbury, Ishaan Gulrajani, Victor Zhong, Romain Paulus, Richard Socher

B696992f 0bbf 4e38 90f8 3114be0658d2Mar 5, 2016·9622 checkouts·arxiv.org

9

Reading Text in the Wild with Convolutional Neural Networks

Max Jaderberg, Karen Simonyan, Andrea Vedaldi, Andrew Zisserman

D7b7240c 3a2d 4d76 bc99 092f474133c2Dec 4, 2014·9601 checkouts·arxiv.org

10

Network In Network

Min Lin, Qiang Chen, Shuicheng Yan

407f85cf 0bdb 4051 9786 5a0f07ce7046Mar 4, 2014·9597 checkouts·arxiv.org

11

Playing Atari with Deep Reinforcement Learning

Volodymyr Mnih, Koray Kavukcuoglu, David Silver, Alex Graves, Ioannis Antonoglou, Daan Wierstra, Martin Riedmiller

D65f9893 cd06 40a8 9a6e e040e5945565Dec 19, 2013·9587 checkouts·arxiv.org

12

SqueezeNet: AlexNet-level accuracy with 50x fewer parameters and <0.5MB model size

Forrest N. Iandola, Song Han, Matthew W. Moskewicz, Khalid Ashraf, William J. Dally, Kurt Keutzer

5c6dada4 0298 4477 8775 cf6b73167cdaNov 4, 2016·9585 checkouts·arxiv.org

13

TensorFlow: Large-Scale Machine Learning on Heterogeneous Distributed Systems

Martín Abadi, Ashish Agarwal, Paul Barham, Eugene Brevdo, Zhifeng Chen, Craig Citro, Greg S. Corrado, Andy Davis, Jeffrey Dean, Matthieu Devin, Sanjay Ghemawat, Ian Goodfellow, Andrew Harp, Geoffrey Irving, Michael Isard, Yangqing Jia, Rafal Jozefowicz, Lukasz Kaiser, Manjunath Kudlur, Josh Levenberg, Dan Mane, Rajat Monga, Sherry Moore, Derek Murray, Chris Olah, Mike Schuster, Jonathon Shlens, Benoit Steiner, Ilya Sutskever, Kunal Talwar, Paul Tucker, Vincent Vanhoucke, Vijay Vasudevan, Fernanda Viegas, Oriol Vinyals, Pete Warden, Martin Wattenberg, Martin Wicke, Yuan Yu, Xiaoqiang Zheng

B11851bf cd47 4c0f 946e 04ccae43d20aMar 16, 2016·9579 checkouts·arxiv.org

14

Caffe: Convolutional Architecture for Fast Feature Embedding

Yangqing Jia, Evan Shelhamer, Jeff Donahue, Sergey Karayev, Jonathan Long, Ross Girshick, Sergio Guadarrama, Trevor Darrell

Fde80f4d bdea 401d a14f 721d97fc6beaJun 20, 2014·9532 checkouts·arxiv.org

15

Distilling the Knowledge in a Neural Network

Geoffrey Hinton, Oriol Vinyals, Jeff Dean

5aeb4413 0a76 4b43 90eb 4002ff1c19e2Mar 9, 2015·9495 checkouts·arxiv.org

16

Learning to Compose Neural Networks for Question Answering

Jacob Andreas, Marcus Rohrbach, Trevor Darrell, Dan Klein

04d69eb8 e0b0 4895 823f ff01a4ef2b04Jun 7, 2016·9467 checkouts·arxiv.org

17

Deep Reinforcement Learning: An Overview

Yuxi Li

02ba3ccc f9ef 4f34 9bf8 4aa0c49d202aJan 26, 2017·9424 checkouts·arxiv.org

18

End-to-End Attention-based Large Vocabulary Speech Recognition

Dzmitry Bahdanau, Jan Chorowski, Dmitriy Serdyuk, Philemon Brakel, Yoshua Bengio

Efcd4bde fe0e 4fd4 9f84 e050e8bfe07aMar 14, 2016·9357 checkouts·arxiv.org

19

Representation Learning: A Review and New Perspectives

Yoshua Bengio, Aaron Courville, Pascal Vincent

88728e20 dbde 411b bff5 0e05f3e0c582Apr 23, 2014·9335 checkouts·arxiv.org

20

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

Ea85884d 7f2f 4e0c bb31 cec5e6f6bcc6Apr 19, 2016·9296 checkouts·arxiv.org

21

Least Squares Generative Adversarial Networks

Xudong Mao, Qing Li, Haoran Xie, Raymond Y. K. Lau, Zhen Wang

636d9540 9169 4229 b131 20aaac8ff363Feb 24, 2017·9292 checkouts·arxiv.org

22

Learning Deconvolution Network for Semantic Segmentation

Hyeonwoo Noh, Seunghoon Hong, Bohyung Han

15418f0b 206c 4c5a a8a5 44f30a48a531May 17, 2015·9287 checkouts·arxiv.org

23

Convolutional Sequence to Sequence Learning

Jonas Gehring, Michael Auli, David Grangier, Denis Yarats, Yann N. Dauphin

Db3fb52b 05c7 4a30 bf28 b7b96dadd513Jul 25, 2017·9257 checkouts·arxiv.org

24

Deep Voice: Real-time Neural Text-to-Speech

Sercan O. Arik, Mike Chrzanowski, Adam Coates, Gregory Diamos, Andrew Gibiansky, Yongguo Kang, Xian Li, John Miller, Andrew Ng, Jonathan Raiman, Shubho Sengupta, Mohammad Shoeybi

F64e6089 450e 4200 84eb 55c3179155ccMar 7, 2017·9257 checkouts·arxiv.org

25

Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks

Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M. Rush, Bart van Merriënboer, Armand Joulin, Tomas Mikolov

E34ae8da 6137 4965 9f45 0d900b2701ecDec 31, 2015·9254 checkouts·arxiv.org

26

MatConvNet - Convolutional Neural Networks for MATLAB

Andrea Vedaldi, Karel Lenc

73370df7 91d0 4883 bfae c976864dd835May 5, 2016·9201 checkouts·arxiv.org

27

Memory Networks

Jason Weston, Sumit Chopra, Antoine Bordes

4548843e a463 4bfe a96a 5129158062feNov 29, 2015·9192 checkouts·arxiv.org

28

Intriguing properties of neural networks

Christian Szegedy, Wojciech Zaremba, Ilya Sutskever, Joan Bruna, Dumitru Erhan, Ian Goodfellow, Rob Fergus

12c2d488 8732 4395 84b8 80a5f92c27c9Feb 19, 2014·9169 checkouts·arxiv.org

29

A Thorough Examination of the CNN/Daily Mail Reading Comprehension Task

Danqi Chen, Jason Bolton, Christopher D. Manning

48055934 3b86 4447 9dcd 1e080481da67Aug 8, 2016·9102 checkouts·arxiv.org

30

Recurrent Models of Visual Attention

Volodymyr Mnih, Nicolas Heess, Alex Graves, Koray Kavukcuoglu

A7fc39f4 2d61 4a2e ad1f 79a4f02972beJun 24, 2014·9074 checkouts·arxiv.org

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How is this “best Awesome List: Deep Learning Foundation Resources” collection ranked?

This page ranks Awesome List: Deep Learning Foundation Resources using topic relevance, checkout momentum, source diversity, and freshness signals. Rankings are recalculated as new items and engagement arrive, so readers see resources that are both high quality and currently useful for implementation, research, and practical decision making. Canonical intent key: topic=al-deep-learning-foundation|type=all|year=evergreen.

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