Yongquan Yang

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 186 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 53 citations into it
• Computer Vision and Pattern Recognition — 41 citations into it
• Model Architectures — 18 citations into it
• Optimization & Training — 13 citations into it
• Information Systems — 6 citations into it
• Molecular Biology — 6 citations into it
• Representation & Self-Supervised Learning — 6 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Yongquan Yang trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Yann LeCun
4. Yoav Freund
5. Kaiming He
6. Leo Breiman
7. Alex Krizhevsky
8. Robert E. Schapire
9. Jerome H. Friedman
10. Christian Szegedy

Papers from Yongquan Yang's perspective

Ordered by how strongly the researchers Yongquan 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
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

• A Survey on ensemble learning under the era of deep learning (2021) — 358 citations