Qiwen Wang

Artificial Intelligence · 2022–2023

A researcher in the Science corpus: 3 papers; trusts 708 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 431 citations into it; #21,288 of 35,345 by trust here, #23,077 by citations
• Computer Vision and Pattern Recognition — 354 citations into it
• Meta & Continual Learning — 290 citations into it
• Representation & Self-Supervised Learning — 91 citations into it
• Optimization & Training — 35 citations into it
• Reinforcement Learning — 23 citations into it
• Model Architectures — 22 citations into it
• Efficiency & Compression — 20 citations into it

Whom Qiwen Wang trusts overall

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

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

Who trusts Qiwen Wang overall

1. Da-Wei Zhou
2. Han-Jia Ye
3. De-chuan Zhan

Papers from Qiwen Wang's perspective

Ordered by how strongly the researchers Qiwen Wang 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. ImageNet: A large-scale hierarchical image database
5. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
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

• Deep Class-Incremental Learning: A Survey (2023) — 133 citations
• Class-Incremental Learning: A Survey (2023) — 380 citations
• A Model or 603 Exemplars: Towards Memory-Efficient Class-Incremental Learning (2022) — 241 citations