Si Wu

Computer Vision and Pattern Recognition · with Cao · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 181 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 59 citations into it
• Artificial Intelligence — 57 citations into it
• Representation & Self-Supervised Learning — 41 citations into it
• Generative Models — 16 citations into it

Whom Si Wu trusts overall

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

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

Who trusts Si Wu overall

1. Umberto Michieli
2. Pietro Zanuttigh

Papers from Si Wu's perspective

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

Their papers

• Model Adaptation: Unsupervised Domain Adaptation Without Source Data (2020) — 585 citations
• Improving Domain-Specific Classification by Collaborative Learning with Adaptation Networks (2019) — 13 citations