#1 · Paper · Mar 22, 2017
Deformable Convolutional Networks
Jifeng Dai, Haozhi Qi, Yuwen Xiong, Yi Li, Guodong Zhang, Han Hu, Yichen Wei · arxiv.org
Best Papers for Machine Learning in March 2017
Track this topic after sign-in.
Query conditions: topic=machine-learning, publish_at in 201703, and type=paper
Top Picks
#2 · Paper · Mar 30, 2017
Batch Renormalization: Towards Reducing Minibatch Dependence in Batch-Normalized Models
Sergey Ioffe · arxiv.org
#3 · Paper · Mar 7, 2017
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 · arxiv.org
#4 · Paper · Mar 10, 2017
Evolution Strategies as a Scalable Alternative to Reinforcement Learning
Tim Salimans, Jonathan Ho, Xi Chen, Ilya Sutskever · arxiv.org
#5 · Paper · Mar 15, 2017
Learning to Discover Cross-Domain Relations with Generative Adversarial Networks
Taeksoo Kim, Moonsu Cha, Hyunsoo Kim, Jungkwon Lee, Jiwon Kim · arxiv.org
#6 · Paper · Mar 5, 2017
Neural Machine Translation and Sequence-to-sequence Models: A Tutorial
Graham Neubig · arxiv.org
#7 · Paper · Mar 22, 2017
Deep Photo Style Transfer
Fujun Luan, Sylvain Paris, Eli Shechtman, Kavita Bala · arxiv.org
#8 · Paper · Mar 3, 2017
On the Origin of Deep Learning
Haohan Wang, Bhiksha Raj · 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.