Ray Chak-Chung Cheung
Computer Vision and Pattern Recognition · 2020
A researcher in the Science corpus: 1 paper; trusts 27 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Computer Vision and Pattern Recognition — 26 citations into it
- Artificial Intelligence — 24 citations into it
- Efficiency & Compression — 24 citations into it
- Model Architectures — 11 citations into it
Whom Ray Chak-Chung Cheung trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Yann LeCun
- Yoshua Bengio
- Diederik P. Kingma
- Geoffrey E. Hinton
- Karen Simonyan
- Kaiming He
- Alex Krizhevsky
- Jimmy Ba
- Ilya Sutskever
- Hanxiao Liu
Papers from Ray Chak-Chung Cheung's perspective
Ordered by how strongly the researchers Ray Chak-Chung Cheung trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Gradient-based learning applied to document recognition
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- ImageNet: A large-scale hierarchical image database
- Going deeper with convolutions
- Learning Multiple Layers of Features from Tiny Images
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)