Chenglin Wu

Artificial Intelligence · 2020–2023

A researcher in the Science corpus: 2 papers; trusts 128 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 40 citations into it
• Computer Vision and Pattern Recognition — 34 citations into it
• Multimodal Learning — 9 citations into it

Whom Chenglin Wu trusts overall

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

1. Kaiming He
2. Diederik P. Kingma
3. Karen Simonyan
4. Geoffrey E. Hinton
5. Ross B. Girshick
6. Alex Krizhevsky
7. Yoshua Bengio
8. Andrew Zisserman
9. Shaoqing Ren
10. Yann LeCun

Papers from Chenglin Wu's perspective

Ordered by how strongly the researchers Chenglin Wu 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. Gradient-based learning applied to document recognition
8. ImageNet: A large-scale hierarchical image database
9. Microsoft COCO: Common Objects in Context
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Multi-Task Collaborative Network for Joint Referring Expression Comprehension and Segmentation (2020) — 370 citations
• MetaGPT: Meta Programming for Multi-Agent Collaborative Framework (2023) — 2,148 citations