Seungwon Lee

Artificial Intelligence · with Behpour · 2020

A researcher in the Science corpus: 1 paper; trusts 58 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 25 citations into it
• Computer Vision and Pattern Recognition — 18 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Model Architectures — 9 citations into it
• Meta & Continual Learning — 5 citations into it

Whom Seungwon Lee trusts overall

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

1. R. Caruana
2. Alex Krizhevsky
3. Kaiming He
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Karen Simonyan
7. Yann LeCun
8. Diederik P. Kingma
9. Quoc V. Le
10. Ilya Sutskever

Who trusts Seungwon Lee overall

1. Haoxuan Qu
2. Seyed Iman Mirzadeh
3. Jingwen Ye
4. Hossein Rahmani
5. Jorge Armando Mendez Mendez
6. Arslan Chaudhry

Papers from Seungwon Lee's perspective

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

Their papers

• Sharing Less is More: Lifelong Learning in Deep Networks with Selective Layer Transfer (2020) — 21 citations