#1 · Paper · Jun 22, 2015
Understanding Neural Networks Through Deep Visualization
Jason Yosinski, Jeff Clune, Anh Nguyen, Thomas Fuchs, Hod Lipson · arxiv.org
Best Papers for Machine Learning in 2015
Track this topic after sign-in.
Query conditions: topic=machine-learning, publish_at in 2015, and type=paper
Top Picks
#2 · Paper · Mar 9, 2015
Distilling the Knowledge in a Neural Network
Geoffrey Hinton, Oriol Vinyals, Jeff Dean · arxiv.org
#3 · Paper · May 17, 2015
Learning Deconvolution Network for Semantic Segmentation
Hyeonwoo Noh, Seunghoon Hong, Bohyung Han · arxiv.org
#4 · Paper · Dec 31, 2015
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 · arxiv.org
#5 · Paper · Nov 29, 2015
Memory Networks
Jason Weston, Sumit Chopra, Antoine Bordes · arxiv.org
#6 · Paper · Dec 1, 2015
Character-Aware Neural Language Models
Yoon Kim, Yacine Jernite, David Sontag, Alexander M. Rush · arxiv.org
#7 · Paper · Sep 2, 2015
A Neural Algorithm of Artistic Style
Leon A. Gatys, Alexander S. Ecker, Matthias Bethge · arxiv.org
#8 · Paper · Dec 8, 2015
Deep Reinforcement Learning with Double Q-learning
Hado van Hasselt, Arthur Guez, David Silver · arxiv.org
#9 · Paper · Dec 10, 2015
Deep Residual Learning for Image Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun · arxiv.org
#10 · Paper · Jul 31, 2015
Image Super-Resolution Using Deep Convolutional Networks
Chao Dong, Chen Change Loy, Kaiming He, Xiaoou Tang · arxiv.org
#11 · Paper · Dec 8, 2015
Deep Speech 2: End-to-End Speech Recognition in English and Mandarin
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 · arxiv.org
#12 · Paper · Jan 30, 2015
ImageNet Large Scale Visual Recognition Challenge
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 · arxiv.org
#13 · Paper · May 30, 2015
Addressing the Rare Word Problem in Neural Machine Translation
Minh-Thang Luong, Ilya Sutskever, Quoc V. Le, Oriol Vinyals, Wojciech Zaremba · arxiv.org
#14 · Paper · Nov 17, 2015
Visualizing and Understanding Recurrent Networks
Andrej Karpathy, Justin Johnson, Li Fei-Fei · arxiv.org
#15 · Paper · Mar 2, 2015
Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift
Sergey Ioffe, Christian Szegedy · arxiv.org
#16 · Paper · Sep 20, 2015
Effective Approaches to Attention-based Neural Machine Translation
Minh-Thang Luong, Hieu Pham, Christopher D. Manning · arxiv.org
#17 · Paper · Jul 22, 2015
A Neural Conversational Model
Oriol Vinyals, Quoc Le · arxiv.org
#18 · Paper · Apr 23, 2015
Spatial Pyramid Pooling in Deep Convolutional Networks for Visual Recognition
Kaiming He, Xiangyu Zhang, Shaoqing Ren, Jian Sun · arxiv.org
#19 · Paper · Apr 2, 2015
Deep Neural Networks are Easily Fooled: High Confidence Predictions for Unrecognizable Images
Anh Nguyen, Jason Yosinski, Jeff Clune · arxiv.org
#20 · Paper · Mar 22, 2015
Retrofitting Word Vectors to Semantic Lexicons
Manaal Faruqui, Jesse Dodge, Sujay K. Jauhar, Chris Dyer, Eduard Hovy, Noah A. Smith · arxiv.org
#21 · Paper · Aug 1, 2015
What makes for effective detection proposals?
Jan Hosang, Rodrigo Benenson, Piotr Dollár, Bernt Schiele · arxiv.org
#22 · Paper · May 20, 2015
DRAW: A Recurrent Neural Network For Image Generation
Karol Gregor, Ivo Danihelka, Alex Graves, Danilo Jimenez Rezende, Daan Wierstra · arxiv.org
#23 · Paper · May 30, 2015
Improved Semantic Representations From Tree-Structured Long Short-Term Memory Networks
Kai Sheng Tai, Richard Socher, Christopher D. Manning · arxiv.org
#24 · Paper · Feb 19, 2015
Recurrent Neural Network Regularization
Wojciech Zaremba, Ilya Sutskever, Oriol Vinyals · arxiv.org
#25 · Paper · Nov 4, 2015
Semi-supervised Sequence Learning
Andrew M. Dai, Quoc V. Le · arxiv.org
#26 · Paper · Apr 10, 2015
Very Deep Convolutional Networks for Large-Scale Image Recognition
Karen Simonyan, Andrew Zisserman · arxiv.org
FAQ
How is this best Machine Learning papers page ranked?
This page ranks Machine Learning papers by topic match, content-type filter, checkout momentum, and freshness. The ranking is recalculated as new items and engagement signals arrive, so the top results stay practical for current workflows instead of remaining static or purely chronological.
What does the time scope in this URL mean?
The time suffix in this URL defines the publish-date window used for ranking. Year paths include items in that year, and YYYYMM paths include one calendar month. This makes comparisons cleaner when you want a focused snapshot rather than an all-time aggregate.
Is this list paid placement?
No. This ranking is editorial and signal-driven, not sponsored placement. Attendemia evaluates public metadata, source context, and usage momentum to rank candidates. Payment does not buy position, so readers can interpret the list as a curation surface rather than advertising inventory.