Stan.Z.Li

Artificial Intelligence · with Gao · 2021

A researcher in the Science corpus: 1 paper; trusts 56 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 50 citations into it
• Computer Vision and Pattern Recognition — 27 citations into it
• Representation & Self-Supervised Learning — 21 citations into it
• Graph Learning — 15 citations into it
• Molecular Biology — 12 citations into it
• Statistical and Nonlinear Physics — 11 citations into it
• Materials Chemistry — 7 citations into it
• Evaluation & Benchmarks — 5 citations into it

Whom Stan.Z.Li trusts overall

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

1. Geoffrey E. Hinton
2. Kaiming He
3. Thomas Kipf
4. Alex Krizhevsky
5. Yoshua Bengio
6. Diederik P. Kingma
7. Max Welling
8. Yann LeCun
9. Ross B. Girshick
10. Ilya Sutskever

Papers from Stan.Z.Li's perspective

Ordered by how strongly the researchers Stan.Z.Li 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Self-Supervised Learning on Graphs: Contrastive, Generative, or Predictive (2021) — 336 citations