Ming Chen

Artificial Intelligence · with Ding · 2020

A researcher in the Science corpus: 1 paper; trusts 13 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 33 citations into it; #34,443 of 35,345 by trust here, #17,412 by citations
• Graph Learning — 18 citations into it; #669 of 693 by trust here, #443 by citations
• Computer Vision and Pattern Recognition — 14 citations into it

Whom Ming Chen trusts overall

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

1. Diederik P. Kingma
2. Kaiming He
3. Johannes Klicpera
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Jimmy Ba
7. Alex Krizhevsky
8. Petar Velickovic
9. Yann LeCun
10. Prithviraj Sen

Who trusts Ming Chen overall

1. Xin Zhou
2. Jing Huang
3. Yao Ma
4. Kaixiong Zhou
5. Seoyoon Kim
6. Jingwen Hu
7. Ruosong Ye
8. Qian Huang
9. Yujun Yan
10. Wei Jin

Papers from Ming Chen's perspective

Ordered by how strongly the researchers Ming Chen 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. ImageNet classification with deep convolutional neural networks
4. Long Short-Term Memory
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Simple and Deep Graph Convolutional Networks (2020) — 1,998 citations