Sungyoon Lee

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 50 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 36 citations into it
• Safety, Robustness & Interpretability — 34 citations into it
• Computer Vision and Pattern Recognition — 11 citations into it
• Hardware and Architecture — 6 citations into it
• Electrical and Electronic Engineering — 5 citations into it
• Program Analysis & Verification — 5 citations into it

Whom Sungyoon Lee trusts overall

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

1. Xiaowei Huang
2. Huan Zhang
3. Aditi Raghunathan
4. Nicholas Carlini
5. Rüdiger Ehlers
6. Krishnamurthy (Dj) Dvijotham
7. Geoffrey E. Hinton
8. J. Kolter
9. Alex Krizhevsky
10. Ian J. Goodfellow

Papers from Sungyoon Lee's perspective

Ordered by how strongly the researchers Sungyoon 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. Gradient-based learning applied to document recognition
5. ImageNet: A large-scale hierarchical image database
6. Long Short-Term Memory
7. Attention is All you Need (Neural Information Processing Systems)
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Lipschitz-Certifiable Training with a Tight Outer Bound (2020) — 21 citations