Qimai Li

Artificial Intelligence · 2018–2020

A researcher in the Science corpus: 5 papers; trusts 95 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 96 citations into it; #7,439 of 35,345 by trust here, #6,378 by citations
• Representation & Self-Supervised Learning — 45 citations into it
• Graph Learning — 44 citations into it; #209 of 693 by trust here, #183 by citations
• Computer Vision and Pattern Recognition — 36 citations into it
• Statistical and Nonlinear Physics — 20 citations into it
• Molecular Biology — 11 citations into it
• Geometry and Topology — 7 citations into it

Whom Qimai Li trusts overall

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

1. Geoffrey E. Hinton
2. Yoshua Bengio
3. Diederik P. Kingma
4. Yann LeCun
5. Alex Krizhevsky
6. Max Welling
7. Ruslan Salakhutdinov
8. Ilya Sutskever
9. Kaiming He
10. Prithviraj Sen

Who trusts Qimai Li overall

1. Junlin Yang
2. Deyu Bo
3. Hao Zhu
4. Uri Alon
5. Chen Cai
6. Lingxiao Zhao
7. Le Wu
8. Yuhui Ding
9. Johannes Klicpera
10. Xiao Wang

Papers from Qimai Li's perspective

Ordered by how strongly the researchers Qimai Li 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. 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. ImageNet Large Scale Visual Recognition Challenge
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Deeper Insights into Graph Convolutional Networks for Semi-Supervised Learning (2018) — 3,507 citations
• Reconstructing Capsule Networks for Zero-shot Intent Classification (2019) — 49 citations
• Label Efficient Semi-Supervised Learning via Graph Filtering (2019) — 179 citations
• Unknown Intent Detection Using Gaussian Mixture Model with an Application to Zero-shot Intent Classification (2020) — 99 citations
• Attributed Graph Clustering via Adaptive Graph Convolution (2019) — 349 citations