Wee Sun Lee

Artificial Intelligence · with Du · 2024–2025

A researcher in the Science corpus: 2 papers; trusts 17 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 43 citations into it
• Reinforcement Learning — 25 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• Computational Theory and Mathematics — 8 citations into it
• Control and Systems Engineering — 7 citations into it
• Management Science and Operations Research — 7 citations into it

Whom Wee Sun Lee trusts overall

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

1. Richard S. Sutton
2. Andrew Barto
3. Jeffrey Scott Vitter
4. Geoffrey E. Hinton
5. Francesco Orabona
6. E. Todorov
7. Andrew W. Moore
8. Yoshua Bengio
9. Alex Krizhevsky
10. Diederik P. Kingma

Papers from Wee Sun Lee's perspective

Ordered by how strongly the researchers Wee Sun 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. Gradient-based learning applied to document recognition
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Human-level control through deep reinforcement learning
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Understanding R1-Zero-Like Training: A Critical Perspective (2025) — 1,176 citations
• Locality Sensitive Sparse Encoding for Learning World Models Online (2024) — 17 citations