Qingfeng Lan

Artificial Intelligence · 2020–2024

A researcher in the Science corpus: 3 papers; trusts 104 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 110 citations into it
• Computer Vision and Pattern Recognition — 52 citations into it
• Reinforcement Learning — 51 citations into it
• Optimization & Training — 31 citations into it
• Meta & Continual Learning — 27 citations into it
• Representation & Self-Supervised Learning — 21 citations into it
• Model Architectures — 18 citations into it
• Efficiency & Compression — 11 citations into it

Whom Qingfeng Lan 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. Kaiming He
8. J. Urgen Schmidhuber
9. Ilya Sutskever
10. Alex Graves

Who trusts Qingfeng Lan overall

1. Che Wang
2. Arsenii Kuznetsov
3. Zijian Zhou
4. Yangchen Pan
5. Pavel Shvechikov

Papers from Qingfeng Lan's perspective

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

Their papers

• Memory-efficient Reinforcement Learning with Knowledge Consolidation (2022) — 4 citations
• Loss of plasticity in deep continual learning (2024) — 353 citations
• Maxmin Q-learning: Controlling the Estimation Bias of Q-learning (2020) — 219 citations