“2016”版本间的差异
来自cslt Wiki
| 第6行： | 第6行： | ||
* [https://arxiv.org/pdf/1512.03385v1.pdf Kaiming He et al. Deep Residual Learning for Image Recognition] | * [https://arxiv.org/pdf/1512.03385v1.pdf Kaiming He et al. Deep Residual Learning for Image Recognition] | ||
* [http://www.isca-speech.org/archive/Interspeech_2016/pdfs/0515.pdf Wei-Ning Hsu et al. Exploiting Depth and Highway Connections in Convolutional Recurrent Deep Neural Networks for Speech Recognition] | * [http://www.isca-speech.org/archive/Interspeech_2016/pdfs/0515.pdf Wei-Ning Hsu et al. Exploiting Depth and Highway Connections in Convolutional Recurrent Deep Neural Networks for Speech Recognition] | ||
| − | * [http://t.cn/RfZHxko MICRO 2016 | + | * [http://t.cn/RfZHxko MICRO 2016 ] |
| + | * [[媒体文件:Cambricon-X.pdf Cambricon-X: An Accelerator for Sparse Neural Networks]] | ||
==Visualization== | ==Visualization== | ||
2016年11月9日 (三) 01:43的版本
DNN architecture
- Ying Zhang et al. Towards End-to-End Speech Recognition with Deep Convolutional Neural Networks
- ICLR2017: OUTRAGEOUSLY LARGE NEURAL NETWORKS: THE SPARSELY-GATED MIXTURE-OF-EXPERTS LAYER
- lightRNN from microsoft
- Kaiming He et al. Deep Residual Learning for Image Recognition
- Wei-Ning Hsu et al. Exploiting Depth and Highway Connections in Convolutional Recurrent Deep Neural Networks for Speech Recognition
- MICRO 2016
- 媒体文件:Cambricon-X.pdf Cambricon-X: An Accelerator for Sparse Neural Networks
Visualization
- Visualizing and Understanding Genomic Sequences Using Deep Neural Networks
- On the Role of Nonlinear Transformations in Deep Neural Network Acoustic Models
Speaker recognition
- INTERSPEECH 2016 Fri-O-2-2 :Special Session: The RedDots Challenge: Towards Characterizing Speakers from Short Utterances
- INTERSPEECH 2016 Fri-O-3-2 : Special Session: The Speakers in the Wild (SITW) Speaker Recognition Challenge
