Yeongwoo Nam

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 62 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 31 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Model Architectures — 6 citations into it
• Optimization & Training — 6 citations into it
• Reinforcement Learning — 5 citations into it

Whom Yeongwoo Nam trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Max Welling
5. Yoshua Bengio
6. Diederik P. Kingma
7. Marc'Aurelio Ranzato
8. Yann LeCun
9. Ilya Sutskever
10. Jia Deng

Papers from Yeongwoo Nam's perspective

Ordered by how strongly the researchers Yeongwoo Nam 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
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

• Confidence Calibration for Incremental Learning (2020) — 3 citations