Yingying Wu

Artificial Intelligence · with Liang · 2022

A researcher in the Science corpus: 1 paper; trusts 83 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 35 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Meta & Continual Learning — 24 citations into it
• Optimization & Training — 7 citations into it
• Representation & Self-Supervised Learning — 7 citations into it

Whom Yingying Wu trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Gido M. van de Ven
6. Yann LeCun
7. Diederik P. Kingma
8. Jia Deng
9. Ross B. Girshick
10. Davide Maltoni

Papers from Yingying Wu's perspective

Ordered by how strongly the researchers Yingying Wu 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. ImageNet: A large-scale hierarchical image database
4. Gradient-based learning applied to document recognition
5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
6. Learning Multiple Layers of Features from Tiny Images
7. Attention is All you Need (Neural Information Processing Systems)
8. ImageNet Large Scale Visual Recognition Challenge
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Long Short-Term Memory

Their papers

• Balancing Between Forgetting and Acquisition in Incremental Subpopulation Learning (2022) — 16 citations