Kuo Yang

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 51 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 61 citations into it
• Artificial Intelligence — 53 citations into it
• Representation & Self-Supervised Learning — 24 citations into it
• Generative Models — 13 citations into it

Whom Kuo Yang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Diederik P. Kingma
6. Yann LeCun
7. Ian J. Goodfellow
8. Ross B. Girshick
9. L. V. D. van der Maaten
10. Ilya Sutskever

Who trusts Kuo Yang overall

1. Liyuan Wang
2. Hongwei Yan
3. Xingxing Zhang

Papers from Kuo Yang's perspective

Ordered by how strongly the researchers Kuo Yang trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Learning Multiple Layers of Features from Tiny Images
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. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Memory Replay with Data Compression for Continual Learning (2022) — 141 citations
• ORDisCo: Effective and Efficient Usage of Incremental Unlabeled Data for Semi-supervised Continual Learning (2021) — 114 citations