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'''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." arXiv preprint arXiv:1601.06759 (2016). *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, arxiv, 2016. 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., 2014. Neural turing machines. arXiv preprint arXiv: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== [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)
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