Yonghua Lin

Artificial Intelligence · with Yan · 2019

A researcher in the Science corpus: 1 paper; trusts 28 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 17 citations into it
• Computer Vision and Pattern Recognition — 17 citations into it
• Model Architectures — 9 citations into it
• Optimization & Training — 9 citations into it

Whom Yonghua Lin trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio

Papers from Yonghua Lin's perspective

Ordered by how strongly the researchers Yonghua Lin 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. Learning Multiple Layers of Features from Tiny Images
3. ImageNet classification with deep convolutional neural networks
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. Attention is All you Need (Neural Information Processing Systems)
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Transferable AutoML by Model Sharing Over Grouped Datasets (2019) — 24 citations