I've been trying to read a paper a day since midsummer. These are a few of the interesting, for me personally, since then:
Generating Sequences With Recurrent Neural Networks - http://arxiv.org/abs/1308.0850
Older one, but important to understand deeply since other recent ideas have come from this!
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks - http://arxiv.org/abs/1511.06434
Unitary Evolution Recurrent Neural Networks - http://arxiv.org/abs/1511.06464
State of the Art Control of Atari Games Using Shallow Reinforcement Learning - http://arxiv.org/abs/1512.01563
Interesting discussion in section 6.1 on the shortcomings/issues of DQN done by Deepmind
Spectral Representations for Convolutional Neural Networks - http://arxiv.org/abs/1506.03767
Deep Residual Learning for Image Recognition - http://arxiv.org/abs/1512.03385
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) - http://arxiv.org/abs/1511.07289
I wish they did more comparisons between similar network architecture with only the units swapped out. Eg. Alexnet, Relu vs Alexnet, Elu.
On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models - http://arxiv.org/abs/1511.09249
Just a few from my list :)
Generating Sequences With Recurrent Neural Networks - http://arxiv.org/abs/1308.0850 Older one, but important to understand deeply since other recent ideas have come from this!
Unsupervised Representation Learning with Deep Convolutional Generative Adversarial Networks - http://arxiv.org/abs/1511.06434
Unitary Evolution Recurrent Neural Networks - http://arxiv.org/abs/1511.06464
State of the Art Control of Atari Games Using Shallow Reinforcement Learning - http://arxiv.org/abs/1512.01563 Interesting discussion in section 6.1 on the shortcomings/issues of DQN done by Deepmind
Spectral Representations for Convolutional Neural Networks - http://arxiv.org/abs/1506.03767
Deep Residual Learning for Image Recognition - http://arxiv.org/abs/1512.03385
Fast and Accurate Deep Network Learning by Exponential Linear Units (ELUs) - http://arxiv.org/abs/1511.07289 I wish they did more comparisons between similar network architecture with only the units swapped out. Eg. Alexnet, Relu vs Alexnet, Elu.
On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models - http://arxiv.org/abs/1511.09249
Just a few from my list :)