Xingjian Li

Artificial Intelligence · with Dou · 2020–2021

A researcher in the Science corpus: 3 papers; trusts 307 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 183 citations into it
• Computer Vision and Pattern Recognition — 113 citations into it
• Safety, Robustness & Interpretability — 62 citations into it
• Efficiency & Compression — 27 citations into it
• Model Architectures — 22 citations into it
• Optimization & Training — 14 citations into it

Whom Xingjian Li trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Kaiming He
5. Yann LeCun
6. Diederik P. Kingma
7. Ilya Sutskever
8. Ruslan Salakhutdinov
9. Karen Simonyan
10. Ross B. Girshick

Who trusts Xingjian Li overall

1. Yifan Zhang
2. Mitchell Wortsman

Papers from Xingjian Li's perspective

Ordered by how strongly the researchers Xingjian Li 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. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• RIFLE: Backpropagation in Depth for Deep Transfer Learning through Re-Initializing the Fully-connected LayEr (2020) — 46 citations
• Interpretable deep learning: interpretation, interpretability, trustworthiness, and beyond (2021) — 507 citations
• Pay Attention to Features, Transfer Learn Faster CNNs (2020) — 83 citations