Yulei Niu

Computer Vision and Pattern Recognition · 2018–2022

A researcher in the Science corpus: 6 papers; trusts 789 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 213 citations into it; #7,518 of 21,575 by trust here, #5,806 by citations
• Artificial Intelligence — 178 citations into it; #13,586 of 35,345 by trust here, #10,207 by citations
• Multimodal Learning — 75 citations into it; #1,126 of 1,211 by trust here, #1,004 by citations
• Representation & Self-Supervised Learning — 47 citations into it
• Natural Language Processing — 37 citations into it
• Causal Inference & Discovery — 22 citations into it; #348 of 364 by trust here, #249 by citations
• Model Architectures — 16 citations into it
• Optimization & Training — 12 citations into it

Whom Yulei Niu trusts overall

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

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

Who trusts Yulei Niu overall

1. Hanwang Zhang
2. Xu Yang
3. Gi-Cheon Kang
4. Xinting Hu
5. Feihong Shen
6. Kaihua Tang
7. Sungjin Park
8. Xiuyi Chen
9. Van-Quang Nguyen
10. Zujie Liang

Papers from Yulei Niu's perspective

Ordered by how strongly the researchers Yulei Niu 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
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. Going deeper with convolutions

Their papers

• Unbiased Scene Graph Generation From Biased Training (2020) — 853 citations
• Recursive Visual Attention in Visual Dialog (2018) — 128 citations
• Prompt-aligned Gradient for Prompt Tuning (2022) — 517 citations
• Counterfactual VQA: A Cause-Effect Look at Language Bias (2020) — 539 citations
• Domain-Adaptive Few-Shot Learning (2020) — 93 citations
• Two Causal Principles for Improving Visual Dialog (2019) — 163 citations