Yingxia Shao

Computer Vision and Pattern Recognition · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 206 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 170 citations into it
• Artificial Intelligence — 151 citations into it
• Generative Models — 127 citations into it
• Statistical and Nonlinear Physics — 39 citations into it
• Probabilistic & Bayesian Methods — 32 citations into it
• Computational Mechanics — 15 citations into it
• Model Architectures — 13 citations into it
• Natural Language Processing — 11 citations into it

Whom Yingxia Shao trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Yann LeCun
6. Kaiming He
7. Leo Breiman
8. Yang Song
9. Ilya Sutskever
10. Radford M. Neal

Papers from Yingxia Shao's perspective

Ordered by how strongly the researchers Yingxia Shao 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. Learning Multiple Layers of Features from Tiny Images
9. GENERATIVE ADVERSARIAL NETS
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Diffusion Models: A Comprehensive Survey of Methods and Applications (2022) — 2,329 citations
• Reliable Data Distillation on Graph Convolutional Network (2020) — 102 citations