Li Yang

Artificial Intelligence · with Fan · 2021–2022

A researcher in the Science corpus: 3 papers; trusts 172 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 73 citations into it
• Computer Vision and Pattern Recognition — 55 citations into it
• Representation & Self-Supervised Learning — 38 citations into it
• Meta & Continual Learning — 29 citations into it
• Reinforcement Learning — 11 citations into it
• Optimization & Training — 9 citations into it
• Model Architectures — 8 citations into it
• Statistical and Nonlinear Physics — 8 citations into it

Whom Li Yang trusts overall

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

1. Alex Krizhevsky
2. Arslan Chaudhry
3. Jaehong Yoon
4. Geoffrey E. Hinton
5. Marc'Aurelio Ranzato
6. Yoshua Bengio
7. Yann LeCun
8. Diederik P. Kingma
9. Kaiming He
10. Oriol Vinyals

Who trusts Li Yang overall

1. Sen Lin
2. Gyuhak Kim
3. Yajing Kong
4. Cheng Chen

Papers from Li Yang's perspective

Ordered by how strongly the researchers Li Yang 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. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
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. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Beyond Not-Forgetting: Continual Learning with Backward Knowledge Transfer (2022) — 81 citations
• TRGP: Trust Region Gradient Projection for Continual Learning (2022) — 116 citations
• GROWN: GRow Only When Necessary for Continual Learning (2021) — 15 citations