Lei Shang

Artificial Intelligence · 2019–2021

A researcher in the Science corpus: 2 papers; trusts 76 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 46 citations into it
• Computer Vision and Pattern Recognition — 42 citations into it
• Representation & Self-Supervised Learning — 31 citations into it
• Computational Mechanics — 7 citations into it
• Model Architectures — 6 citations into it
• Scaling & Learning Theory — 5 citations into it

Whom Lei Shang trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Kaiming He
4. Yoshua Bengio
5. Christian Szegedy
6. J. Urgen Schmidhuber
7. Ilya Sutskever
8. Yann LeCun
9. Diederik P. Kingma
10. Sergey Ioffe

Who trusts Lei Shang overall

1. Arthur Douillard

Papers from Lei Shang's perspective

Ordered by how strongly the researchers Lei Shang 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. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Attention is All you Need (Neural Information Processing Systems)
8. Learning Multiple Layers of Features from Tiny Images
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• SoftTriple Loss: Deep Metric Learning Without Triplet Sampling (2019) — 432 citations
• Dash: Semi-Supervised Learning with Dynamic Thresholding (2021) — 300 citations