Tian Ye

Computer Vision and Pattern Recognition · with Davidson · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 41 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 21 citations into it
• Artificial Intelligence — 19 citations into it
• Computational Mechanics — 9 citations into it; #7,137 of 10,001 by trust here, #9,582 by citations

Whom Tian Ye trusts overall

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

1. Geoffrey E. Hinton
2. Rong Ge
3. Yann LeCun
4. Nitish Srivastava
5. Alex Krizhevsky
6. Simon Shaolei Du
7. Yoshua Bengio
8. Diederik P. Kingma
9. Jiajun Wu
10. Jason D. Lee

Who trusts Tian Ye overall

1. Binghui Peng
2. Andrej Risteski
3. Liangzu Peng

Papers from Tian Ye's perspective

Ordered by how strongly the researchers Tian Ye 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Global Convergence of Gradient Descent for Asymmetric Low-Rank Matrix Factorization (2021) — 60 citations
• Interpretable Intuitive Physics Model (2018) — 58 citations