Ning Xu

Artificial Intelligence · with Lin · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 153 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 58 citations into it
• Computer Vision and Pattern Recognition — 57 citations into it
• Representation & Self-Supervised Learning — 29 citations into it
• Optimization & Training — 10 citations into it
• Reinforcement Learning — 6 citations into it

Whom Ning Xu trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Ross B. Girshick
6. Yoshua Bengio
7. Yann LeCun
8. Jimmy Ba
9. Ilya Sutskever
10. X. Zhang

Papers from Ning Xu's perspective

Ordered by how strongly the researchers Ning Xu 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. ImageNet Large Scale Visual Recognition Challenge
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
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

• Delving into the Cyclic Mechanism in Semi-supervised Video Object Segmentation (2020) — 32 citations
• Learngene: From Open-World to Your Learning Task (2021) — 43 citations