2017年11月16日 (四) 03:08的版本

SaturnLab-学术活动

2017年学术活动

• 2017年11月18日

宋丹丹：

• 2017年11月11日

闫泽禹：

[x] "Dynamic Routing Between Capsules", S. Sabour, N. Frosst and G.E. Hinton, https://arxiv.org/abs/1710.09829

• 2017年11月04日

常嘉辉：GAN

[x] Generative Adversarial Networks: An Overview, https://arxiv.org/abs/1710.07035.

• 2017年10月28日

陆昕：PixelRNN

[x] Oord, Aaron van den, Nal Kalchbrenner, and Koray Kavukcuoglu. "Pixel recurrent neural networks." https://arxiv.org/abs/1601.06759.

• 2017年10月21日

冯 杰：DeepST

[x] Deep Spatio-Temporal Residual Networks for Citywide Crowd Flows Prediction, AAAI 2017.

议题： AlphaGo Zero

[x] David Silver, Mastering the game of Go without human knowledge, nature 2017

[x] Xilinx Inc., Introduction to FPGA Design with Vivado High-Level Synthesis, UG998, 2013.

• 2017年10月14日

宋丹丹： [x] Matthieu Courbariaux et al., Binarized Neural Networks: Training Neural Networks withWeights and Activations Constrained to +1 or -1, https://arxiv.org/abs/1602.02830.

贺子航： [x] E. Nurvitadhi et al., Accelerating Binarized Neural Networks: Comparison of FPGA, CPU, GPU, and ASIC, International Conference on Field-Programmable Technology (FPT), pp. 77-84, 2016.

陈 震： [x] Umuroglu, Yaman et al., FINN: A Framework for Fast, Scalable Binarized Neural Network Inference, ACM/SIGDA International Symposium on Field-Programmable Gate Arrays(FPGA), pp.65-74, 2017.

• 2017年10月7日

柳 荫： [x] Huang, Gao, Zhuang Liu, Kilian Q. Weinberger, and Laurens van der Maaten, Densely Connected Convolutional Networks, CVPR 2017.

陈 震： [x] Annett Ungethüm et al., Overview on Hardware Optimizations for Database Engines, BTW 2017.

• 2017年9月30日

郑文勋： [x] Graves, A., Wayne, G. and Danihelka, I., Neural turing machines. https://arxiv.org/abs/1410.5401.

陈 震： [x] Jouppi, N.P. et al., In-Datacenter Performance Analysis of a Tensor Processing Unit, ISCA 2017.

• 2017年9月23日

陈 震： [x] Jeff. Dean et al., Large scale distributed deep networks. In Advances in neural information processing systems, pp. 1223-1231, 2012.

• 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 scale distributed 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.

TFX - A TensorFlow-Based Production-Scale Machine Learning Platform, kdd2017.

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

Voting for Voting in Online Point Cloud Object Detection

3D object proposal for object class detection

3D Fully Convolutional Network for Vehicle Detection in Point Cloud

Vehicle Detection from 3D Lidar Using Fully Convolutional Network

Multi-View 3D Object Detection Network for Autonomous Driving

[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)