Xingyi Yang

Computer Vision and Pattern Recognition · 2020–2024

A researcher in the Science corpus: 5 papers; trusts 386 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 143 citations into it
• Artificial Intelligence — 126 citations into it; #24,093 of 35,345 by trust here, #24,417 by citations
• Representation & Self-Supervised Learning — 45 citations into it
• Generative Models — 20 citations into it
• Model Architectures — 13 citations into it
• Optimization & Training — 11 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Media Technology — 8 citations into it

Whom Xingyi Yang trusts overall

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

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

Who trusts Xingyi Yang overall

1. Dongze Lian
2. Ahmad Chaddad
3. Sakshi Ahuja
4. Xin He
5. Yu-Huan Wu
6. Michael James Horry
7. Enrique Tomás Martínez Beltrán
8. Feng Shi
9. Daquan Zhou
10. Xinchao Wang

Papers from Xingyi Yang's perspective

Ordered by how strongly the researchers Xingyi Yang 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. Gradient-based learning applied to document recognition
7. Long Short-Term Memory
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

• Sample-Efficient Deep Learning for COVID-19 Diagnosis Based on CT Scans (2020) — 393 citations
• Learning with Recoverable Forgetting (2022) — 53 citations
• OminiControl: Minimal and Universal Control for Diffusion Transformer (2024) — 336 citations
• Factorizing Knowledge in Neural Networks (2022) — 136 citations
• COVID-CT-Dataset: A CT Scan Dataset about COVID-19 (2020) — 910 citations