Chen-Yi Lee

Artificial Intelligence · 2020–2021

A researcher in the Science corpus: 2 papers; trusts 550 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 68 citations into it
• Computer Vision and Pattern Recognition — 67 citations into it
• Efficiency & Compression — 25 citations into it
• Model Architectures — 25 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Optimization & Training — 11 citations into it
• Meta & Continual Learning — 9 citations into it

Whom Chen-Yi Lee trusts overall

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

1. Alex Krizhevsky
2. Kaiming He
3. Geoffrey E. Hinton
4. Yann LeCun
5. Yoshua Bengio
6. Karen Simonyan
7. Christian Szegedy
8. Diederik P. Kingma
9. Ilya Sutskever
10. Ross B. Girshick

Papers from Chen-Yi Lee's perspective

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

Their papers

• Few-Shot and Continual Learning with Attentive Independent Mechanisms (2021) — 34 citations
• NeuralScale: Efficient Scaling of Neurons for Resource-Constrained Deep Neural Networks (2020) — 15 citations