Yan Luo

Computer Vision and Pattern Recognition · 2 papers · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 286 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 66 citations into it
• Artificial Intelligence — 57 citations into it
• Representation & Self-Supervised Learning — 21 citations into it
• Optimization & Training — 18 citations into it
• Meta & Continual Learning — 17 citations into it
• Model Architectures — 6 citations into it

Whom Yan Luo trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Kaiming He
5. L. Eon Bottou
6. Yann LeCun
7. Yoshua Bengio
8. Oriol Vinyals
9. Ilya Sutskever
10. Jimmy Ba

Papers from Yan Luo's perspective

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

Their papers

• Embracing Uncertainty: Decoupling and De-bias for Robust Temporal Grounding (2021) — 61 citations
• Learning to Predict Gradients for Semi-Supervised Continual Learning (2022) — 14 citations