Tian Tan

Artificial Intelligence · 2014–2017

A researcher in the Science corpus: 4 papers; trusts 54 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 72 citations into it; #20,214 of 35,345 by trust here, #13,163 by citations
• Signal Processing — 64 citations into it; #4,160 of 7,572 by trust here, #1,904 by citations
• Speech & Audio — 34 citations into it; #827 of 1,076 by trust here, #797 by citations
• Computer Vision and Pattern Recognition — 16 citations into it
• Natural Language Processing — 15 citations into it
• Model Architectures — 12 citations into it; #1,747 of 2,278 by trust here, #1,794 by citations
• Efficiency & Compression — 6 citations into it

Whom Tian Tan trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Dong Yu
2. Geoffrey E. Hinton
3. George E. Dahl
4. Abdel-rahman Mohamed
5. Yann LeCun
6. Ossama Abdel-Hamid
7. Andrew W. Senior
8. Li Deng
9. Yoshua Bengio
10. Alex Krizhevsky

Who trusts Tian Tan overall

1. Khe Chai Sim
2. Lahiru Samarakoon
3. Sibo Tong
4. Chunyang Wu
5. Wayne Xiong
6. Philip N. Garner
7. Andreas Stolcke
8. Jasha Droppo
9. Dong Yu
10. Panagiota Karanasou

Papers from Tian Tan's perspective

Ordered by how strongly the researchers Tian Tan trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
8. ImageNet: A large-scale hierarchical image database
9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Very Deep Convolutional Neural Networks for Noise Robust Speech Recognition (2016) — 332 citations
• Reshaping deep neural network for fast decoding by node-pruning (2014) — 121 citations
• Cluster adaptive training for deep neural network (2015) — 75 citations
• Adaptation of Deep Neural Network Acoustic Models for Robust Automatic Speech Recognition (2017) — 14 citations