Sen Lin

Artificial Intelligence · with Yang · 2020–2022

A researcher in the Science corpus: 4 papers; trusts 186 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 90 citations into it; #31,655 of 35,345 by trust here, #21,878 by citations
• Computer Vision and Pattern Recognition — 61 citations into it
• Representation & Self-Supervised Learning — 41 citations into it
• Meta & Continual Learning — 31 citations into it
• Reinforcement Learning — 13 citations into it
• Optimization & Training — 12 citations into it
• Model Architectures — 8 citations into it
• Radiology, Nuclear Medicine and Imaging — 8 citations into it

Whom Sen Lin trusts overall

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

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

Who trusts Sen Lin overall

1. Marvin Zhang
2. Mang Ye
3. Gyuhak Kim
4. Yajing Kong
5. Cheng Chen
6. Liangzu Peng
7. Liyuan Wang
8. Alireza Fallah
9. Li Yang
10. Xiuwen Fang

Papers from Sen Lin's perspective

Ordered by how strongly the researchers Sen Lin trusts endorse each paper. Same corpus, a different order for every researcher.

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
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. 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

• A Collaborative Learning Framework via Federated Meta-Learning (2020) — 95 citations
• 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