Mu Cai

Computer Vision and Pattern Recognition · 2022–2024

A researcher in the Science corpus: 2 papers; trusts 198 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 59 citations into it
• Artificial Intelligence — 58 citations into it
• Model Architectures — 10 citations into it
• Safety, Robustness & Interpretability — 8 citations into it

Whom Mu Cai trusts overall

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

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

Papers from Mu Cai's perspective

Ordered by how strongly the researchers Mu Cai 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. 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

• LLaVA-Prumerge: Adaptive Token Reduction for Efficient Large Multimodal Models (2024) — 376 citations
• VOS: Learning What You Don't Know by Virtual Outlier Synthesis (2022) — 447 citations