Jiechao Guan

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 2 papers; trusts 193 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 78 citations into it
• Computer Vision and Pattern Recognition — 75 citations into it
• Representation & Self-Supervised Learning — 45 citations into it
• Model Architectures — 5 citations into it

Whom Jiechao Guan trusts overall

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

1. Kaiming He
2. Geoffrey E. Hinton
3. Karen Simonyan
4. Alex Krizhevsky
5. Yoshua Bengio
6. Ilya Sutskever
7. Diederik P. Kingma
8. Andrew Zisserman
9. Yann LeCun
10. Christian Szegedy

Papers from Jiechao Guan's perspective

Ordered by how strongly the researchers Jiechao Guan 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
6. ImageNet Large Scale Visual Recognition Challenge
7. Gradient-based learning applied to document recognition
8. Long Short-Term Memory
9. Going deeper with convolutions
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Domain-Adaptive Few-Shot Learning (2020) — 93 citations
• Domain-Invariant Projection Learning for Zero-Shot Recognition (2018) — 50 citations