Min Shi

Artificial Intelligence · with Huang · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 47 citations into it
• Graph Learning — 18 citations into it

Whom Min Shi trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Yoshua Bengio
4. Alessio Micheli
5. Barret Zoph
6. Ilya Sutskever
7. Diederik P. Kingma
8. Thomas Kipf
9. Nitish Srivastava
10. Kaiming He

Who trusts Min Shi overall

1. Kaixiong Zhou
2. Qingquan Song

Papers from Min Shi's perspective

Ordered by how strongly the researchers Min Shi 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
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

• Genetic-GNN: Evolutionary architecture search for Graph Neural Networks (2022) — 66 citations
• Evolutionary Architecture Search for Graph Neural Networks (2020) — 24 citations