Yingxue Pang

Computer Vision and Pattern Recognition · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 403 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 145 citations into it
• Generative Models — 75 citations into it
• Artificial Intelligence — 46 citations into it
• Representation & Self-Supervised Learning — 14 citations into it
• Probabilistic & Bayesian Methods — 10 citations into it
• Optimization & Training — 7 citations into it

Whom Yingxue Pang trusts overall

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

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

Papers from Yingxue Pang's perspective

Ordered by how strongly the researchers Yingxue Pang 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. Going deeper with convolutions
10. GENERATIVE ADVERSARIAL NETS

Their papers

• AIM 2020 Challenge on Real Image Super-Resolution: Methods and Results (2020) — 43 citations
• Image-to-Image Translation: Methods and Applications (2021) — 349 citations