Zhongxiao Li

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 127 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 91 citations into it
• Molecular Biology — 66 citations into it
• Computer Vision and Pattern Recognition — 59 citations into it
• Model Architectures — 27 citations into it
• Representation & Self-Supervised Learning — 18 citations into it
• Computational Biology & Bioinformatics — 17 citations into it
• Optimization & Training — 17 citations into it
• Generative Models — 9 citations into it

Whom Zhongxiao Li trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Ilya Sutskever
5. Yoshua Bengio
6. Yann LeCun
7. Diederik P. Kingma
8. Karen Simonyan
9. Christian Szegedy
10. Ross B. Girshick

Who trusts Zhongxiao Li overall

1. Felipe Kenji Nakano
2. Onur Tasar

Papers from Zhongxiao Li's perspective

Ordered by how strongly the researchers Zhongxiao 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. Gradient-based learning applied to document recognition
6. ImageNet: A large-scale hierarchical image database
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Going deeper with convolutions
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Deep learning in bioinformatics: introduction, application, and perspective in big data era (2019) — 335 citations
• SupportNet: solving catastrophic forgetting in class incremental learning with support data (2018) — 31 citations