Jinkun Lin

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 15 citations into it
• Computer Vision and Pattern Recognition — 10 citations into it
• ML Systems & Hardware — 10 citations into it
• Computer Networks and Communications — 7 citations into it

Whom Jinkun Lin trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Xiangru Lian
4. Pitch Patarasuk
5. Martin A. Zinkevich
6. Ce Zhang
7. Mark Everingham
8. Jianmin Chen
9. Kaiming He
10. Ross B. Girshick

Papers from Jinkun Lin's perspective

Ordered by how strongly the researchers Jinkun 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. Learning Multiple Layers of Features from Tiny Images
4. Going deeper with convolutions
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. ImageNet: A large-scale hierarchical image database
9. Attention is All you Need (Neural Information Processing Systems)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Hop: Heterogeneity-aware Decentralized Training (2019) — 61 citations