Hujun Yin

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 68 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it
• Computer Vision and Pattern Recognition — 29 citations into it
• Optimization & Training — 22 citations into it
• Model Architectures — 12 citations into it
• Reinforcement Learning — 7 citations into it

Whom Hujun Yin trusts overall

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

1. Geoffrey E. Hinton
2. J. Urgen Schmidhuber
3. Yoshua Bengio
4. Diederik P. Kingma
5. Yann LeCun
6. Sepp Hochreiter
7. James Martens
8. Kaiming He
9. Alex Krizhevsky
10. Ilya Sutskever

Papers from Hujun Yin's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Meta-Learning with Warped Gradient Descent (2019) — 221 citations