Weiming Zhuang

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 2 papers; trusts 208 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 62 citations into it
• Computer Vision and Pattern Recognition — 53 citations into it
• Representation & Self-Supervised Learning — 28 citations into it
• Meta & Continual Learning — 19 citations into it
• Federated & Distributed Learning — 14 citations into it
• Reinforcement Learning — 5 citations into it

Whom Weiming Zhuang trusts overall

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

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

Papers from Weiming Zhuang's perspective

Ordered by how strongly the researchers Weiming Zhuang 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. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Long Short-Term Memory
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Collaborative Unsupervised Visual Representation Learning from Decentralized Data (2021) — 130 citations
• TARGET: Federated Class-Continual Learning via Exemplar-Free Distillation (2023) — 118 citations