Cheng He

Artificial Intelligence · with Cheng · 2019–2021

A researcher in the Science corpus: 3 papers; trusts 168 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it
• Computational Theory and Mathematics — 62 citations into it
• Computer Vision and Pattern Recognition — 55 citations into it
• Management Science and Operations Research — 16 citations into it
• Model Architectures — 12 citations into it
• Optimization & Training — 9 citations into it

Whom Cheng He trusts overall

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

1. Kalyanmoy Deb
2. Yaochu Jin
3. Eckart Zitzler
4. Kaiming He
5. Qingfu Zhang
6. Joshua D. Knowles
7. Ran Cheng
8. Ross B. Girshick
9. Paul J. Werbos
10. Geoffrey E. Hinton

Papers from Cheng He's perspective

Ordered by how strongly the researchers Cheng He 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. ImageNet: A large-scale hierarchical image database
4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
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. Going deeper with convolutions
9. GENERATIVE ADVERSARIAL NETS
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• FaPN: Feature-aligned Pyramid Network for Dense Image Prediction (2021) — 262 citations
• A Classification-Based Surrogate-Assisted Evolutionary Algorithm for Expensive Many-Objective Optimization (2019) — 302 citations
• Evolutionary Large-Scale Multi-Objective Optimization: A Survey (2021) — 426 citations