Tianyao Chen

Artificial Intelligence · 2017

A researcher in the Science corpus: 2 papers; trusts 53 researchers and is trusted by 31 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 51 citations into it; #6,785 of 35,345 by trust here, #6,330 by citations
• Computer Vision and Pattern Recognition — 34 citations into it; #4,968 of 21,575 by trust here, #4,658 by citations
• Model Architectures — 28 citations into it
• Optimization & Training — 27 citations into it
• Reinforcement Learning — 13 citations into it; #1,404 of 2,242 by trust here, #1,705 by citations
• Neural Architecture Search & AutoML — 10 citations into it; #63 of 283 by trust here, #41 by citations
• Natural Language Processing — 8 citations into it

Whom Tianyao Chen trusts overall

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

1. Ronald J. Williams
2. Alex Krizhevsky
3. Yoshua Bengio
4. Ilya Sutskever
5. Geoffrey E. Hinton
6. James Bergstra
7. Diederik P. Kingma
8. Sergey Ioffe
9. Sham M. Kakade
10. Kaiming He

Who trusts Tianyao Chen overall

1. Martin Wistuba
2. Xuanyi Dong
3. Han Cai
4. Thomas Elsken
5. Yanan Sun
6. Haifeng Jin
7. Yihui He
8. Song Han
9. Hang Xu
10. Sandro Skansi

Papers from Tianyao Chen's perspective

Ordered by how strongly the researchers Tianyao Chen 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Going deeper with convolutions

Their papers

• Efficient Architecture Search by Network Transformation (2017) — 633 citations
• Reinforcement Learning for Architecture Search by Network Transformation (2017) — 67 citations