Eugene 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 Eugene Lee trusts overall

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

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

Who trusts Eugene Lee overall

1. Jaya Kalla

Papers from Eugene Lee's perspective

Ordered by how strongly the researchers Eugene 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. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Going deeper with convolutions

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