Ge Wang

Computer Vision and Pattern Recognition · with Li · 2022

A researcher in the Science corpus: 1 paper; trusts 25 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 38 citations into it
• Artificial Intelligence — 33 citations into it
• Representation & Self-Supervised Learning — 12 citations into it

Whom Ge Wang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Ian J. Goodfellow
4. Ilya Sutskever
5. Kaiming He
6. Yoshua Bengio
7. David Berthelot
8. Ilya Loshchilov
9. Yann LeCun
10. Diederik P. Kingma

Papers from Ge Wang's perspective

Ordered by how strongly the researchers Ge Wang 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. Learning Multiple Layers of Features from Tiny Images
4. ImageNet Large Scale Visual Recognition Challenge
5. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
8. Long Short-Term Memory
9. Attention is All you Need (Neural Information Processing Systems)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Decoupled Mixup for Data-efficient Learning (2022) — 20 citations