2017年10月6日 (五) 14:18的版本

2017年学术活动

2017年10月7日

柳荫： XXXX

2017年9月30日郑文勋： [x] Graves, A., Wayne, G. and Danihelka, I., 2014. Neural turing machines. arXiv preprint arXiv:1410.5401.

2017年5月21日

郑文勋：

[x] Yu Su et al., In-Situ Bitmaps Generation and Efficient Data Analysis based on Bitmaps, HPDC 2015.

2017年4月8日

郑文勋：

[x] Nguyen, Anh, Jason Yosinski, and Jeff Clune. "Deep neural networks are easily fooled: High confidence predictions for unrecognizable images." CVPR. 2015.

供选论文清单

TensorFlow系列

DistBelief - large deep networks, nips 2012.

TensorFlow: A system for large-scale machine learning, OSDI 2016.

TPU - In-Datacenter Performance Analysis of a Tensor Processing Unit, ISCA 2017.

CV系列

Densely Connected Convolutional Networks,CVPR 2017.

ASR语音识别

Multichannel Signal Processing with Deep Neural Networks for Automatic Speech Recognition-TASLP-2017

XXXX

[Quasi-Recurrent Neural Networks](https://arxiv.org/abs/1611.01576)

[Training RNNs as Fast as CNNs](https://arxiv.org/abs/1709.02755)

[Semi-Supervised Classification with Graph Convolutional Networks](https://arxiv.org/abs/1609.02907)

[A Survey on Transfer Learning](http://www3.ntu.edu.sg/home/sinnopan/publications/TLsurvey_0822.pdf)

[How transferable are features in deep neuralnetworks?](https://arxiv.org/abs/1411.1792)

[Progressive Neural Networks](https://arxiv.org/abs/1606.04671)

[One-Shot Learning of Object Categories](http://vision.stanford.edu/documents/Fei-FeiFergusPerona2006.pdf)

[One-shot Learning with Memory-Augmented Neural Networks](https://arxiv.org/abs/1605.06065)

[Auto-Encoding Variational Bayes](https://arxiv.org/abs/1312.6114)

[Autoencoding beyond pixels using a learned similarity metric](https://arxiv.org/abs/1512.09300)

“Student-Research-Training-THU”版本间的差异