1
Understanding Neural Networks Through Deep Visualization
Source ↗Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, Hod Lipson
Jun 22, 2015·9801 checkouts·arxiv.org
Best Machine Learning Papers for 2015
The highest-signal papers on Machine Learning, ranked by community reviews and momentum.
Canonical intent: topic=machine-learning|type=paper|year=2015
Top Picks
2
Distilling the Knowledge in a Neural Network
Source ↗Geoffrey Hinton, Oriol Vinyals, Jeff Dean
Mar 9, 2015·9495 checkouts·arxiv.org
3
Learning Deconvolution Network for Semantic Segmentation
Source ↗Hyeonwoo Noh, Seunghoon Hong, Bohyung Han
May 17, 2015·9287 checkouts·arxiv.org
4
Towards AI-Complete Question Answering: A Set of Prerequisite Toy Tasks
Source ↗Jason Weston, Antoine Bordes, Sumit Chopra, Alexander M. Rush, Bart van Merriënboer, Armand Joulin, Tomas Mikolov
Dec 31, 2015·9254 checkouts·arxiv.org
5
6
Character-Aware Neural Language Models
Source ↗Yoon Kim, Yacine Jernite, David Sontag, Alexander M. Rush
Dec 1, 2015·8688 checkouts·arxiv.org
7
A Neural Algorithm of Artistic Style
Source ↗Leon A. Gatys, Alexander S. Ecker, Matthias Bethge
Sep 2, 2015·8063 checkouts·arxiv.org
8
Deep Reinforcement Learning with Double Q-learning
Source ↗Hado van Hasselt, Arthur Guez, David Silver
Dec 8, 2015·7936 checkouts·arxiv.org
9
Deep Residual Learning for Image Recognition
Source ↗Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Dec 10, 2015·7861 checkouts·arxiv.org
10
Image Super-Resolution Using Deep Convolutional Networks
Source ↗Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang
Jul 31, 2015·7703 checkouts·arxiv.org
11
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
Source ↗Dario Amodei, Rishita Anubhai, Eric Battenberg, Carl Case, Jared Casper, Bryan Catanzaro, Jingdong Chen, Mike Chrzanowski, Adam Coates, Greg Diamos, Erich Elsen, Jesse Engel, Linxi Fan, Christopher Fougner, Tony Han, Awni Hannun, Billy Jun, Patrick LeGresley, Libby Lin, Sharan Narang, Andrew Ng, Sherjil Ozair, Ryan Prenger, Jonathan Raiman, Sanjeev Satheesh, David Seetapun, Shubho Sengupta, Yi Wang, Zhiqian Wang, Chong Wang, Bo Xiao, Dani Yogatama, Jun Zhan, Zhenyao Zhu
Dec 8, 2015·7681 checkouts·arxiv.org
12
ImageNet Large Scale Visual Recognition Challenge
Source ↗Olga Russakovsky, Jia Deng, Hao Su, Jonathan Krause, Sanjeev Satheesh, Sean Ma, Zhiheng Huang, Andrej Karpathy, Aditya Khosla, Michael Bernstein, Alexander C. Berg, Li Fei-Fei
Jan 30, 2015·7310 checkouts·arxiv.org
13
Addressing the Rare Word Problem in Neural Machine Translation
Source ↗Minh-Thang Luong, Ilya Sutskever, Quoc V. Le, Oriol Vinyals, Wojciech Zaremba
May 30, 2015·7250 checkouts·arxiv.org
14
Visualizing and Understanding Recurrent Networks
Source ↗Andrej Karpathy, Justin Johnson, Li Fei-Fei
Nov 17, 2015·7168 checkouts·arxiv.org
15
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Source ↗Sergey Ioffe, Christian Szegedy
Mar 2, 2015·7006 checkouts·arxiv.org
16
Effective Approaches to Attention-based Neural Machine Translation
Source ↗Minh-Thang Luong, Hieu Pham, Christopher D. Manning
Sep 20, 2015·6875 checkouts·arxiv.org
17
18
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Source ↗Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun
Apr 23, 2015·6580 checkouts·arxiv.org
19
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Source ↗Anh Nguyen, Jason Yosinski, Jeff Clune
Apr 2, 2015·6431 checkouts·arxiv.org
20
Retrofitting Word Vectors to Semantic Lexicons
Source ↗Manaal Faruqui, Jesse Dodge, Sujay K. Jauhar, Chris Dyer, Eduard Hovy, Noah A. Smith
Mar 22, 2015·6392 checkouts·arxiv.org
21
What makes for effective detection proposals?
Source ↗Jan Hosang, Rodrigo Benenson, Piotr Dollár, Bernt Schiele
Aug 1, 2015·6321 checkouts·arxiv.org
22
DRAW: A Recurrent Neural Network For Image Generation
Source ↗Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra
May 20, 2015·5807 checkouts·arxiv.org
23
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
Source ↗Kai Sheng Tai, Richard Socher, Christopher D. Manning
May 30, 2015·5800 checkouts·arxiv.org
24
Recurrent Neural Network Regularization
Source ↗Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals
Feb 19, 2015·5426 checkouts·arxiv.org
25
26
Very Deep Convolutional Networks for Large-Scale Image Recognition
Source ↗Karen Simonyan, Andrew Zisserman
Apr 10, 2015·5097 checkouts·arxiv.org
FAQ
How is this “best Machine Learning Papers” collection ranked?
This page ranks Machine Learning Papers 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=machine-learning|type=paper|year=2015.
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Attendemia maps each slug variant, including best-of and year forms, to one canonical intent key. If two URLs describe the same topic, type, and timeframe, non-canonical versions permanently redirect. This consolidates crawl signals, avoids duplicate content dilution, and helps search engines index the strongest single page.
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Are these paid recommendations?
No. These recommendations are not paid placements. Attendemia ranks items from public metadata, source quality coverage, and user engagement signals, then orders them by practical usefulness. Sponsorship does not buy rank position, so this page should be interpreted as editorial curation rather than advertising inventory.