Jun Luo

Artificial Intelligence · with Lan · 2022

A researcher in the Science corpus: 1 paper; trusts 59 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it
• Reinforcement Learning — 26 citations into it
• Computer Vision and Pattern Recognition — 21 citations into it
• Meta & Continual Learning — 19 citations into it
• Optimization & Training — 9 citations into it
• Generative Models — 5 citations into it

Whom Jun Luo trusts overall

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

1. Geoffrey E. Hinton
2. Richard S. Sutton
3. Yoshua Bengio
4. Diederik P. Kingma
5. Alex Krizhevsky
6. Yann LeCun
7. J. Urgen Schmidhuber
8. Kaiming He
9. Rahaf Aljundi
10. John Schulman

Papers from Jun Luo's perspective

Ordered by how strongly the researchers Jun Luo 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. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Memory-efficient Reinforcement Learning with Knowledge Consolidation (2022) — 4 citations