Keeheon Lee

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 248 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 64 citations into it
• Computer Vision and Pattern Recognition — 58 citations into it
• Scaling & Learning Theory — 13 citations into it
• Efficiency & Compression — 12 citations into it
• Model Architectures — 9 citations into it
• Representation & Self-Supervised Learning — 6 citations into it

Whom Keeheon Lee trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. David G. Lowe
5. Yoshua Bengio
6. Ilya Sutskever
7. Yann LeCun
8. Diederik P. Kingma
9. Ross B. Girshick
10. Sepp Hochreiter

Papers from Keeheon Lee's perspective

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

Their papers

• The Computational Limits of Deep Learning (2020) — 707 citations