Wei Li

Artificial Intelligence · 2 papers · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 60 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it
• Computer Vision and Pattern Recognition — 45 citations into it
• Representation & Self-Supervised Learning — 15 citations into it
• Optimization & Training — 7 citations into it
• Computer Networks and Communications — 6 citations into it

Whom Wei Li trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. Alex Krizhevsky
5. Yoshua Bengio
6. Yann LeCun
7. Ross B. Girshick
8. Ilya Sutskever
9. X. Zhang
10. Shaoqing Ren

Papers from Wei Li's perspective

Ordered by how strongly the researchers Wei 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. ImageNet: A large-scale hierarchical image database
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Learning Multiple Layers of Features from Tiny Images
9. ImageNet Large Scale Visual Recognition Challenge
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Semi-Supervised Semantic Segmentation Using Unreliable Pseudo-Labels (2022) — 511 citations
• FastFlow: Unsupervised Anomaly Detection and Localization via 2D Normalizing Flows (2021) — 475 citations