Yudong Cao

Artificial Intelligence · with Ding · 2021

A researcher in the Science corpus: 2 papers; trusts 23 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Control and Systems Engineering — 20 citations into it
• Model Architectures — 17 citations into it
• Computer Vision and Pattern Recognition — 16 citations into it
• Mechanical Engineering — 14 citations into it
• Mechanics of Materials — 5 citations into it
• Optimization & Training — 5 citations into it

Whom Yudong Cao trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Jimmy Ba
4. Kaiming He
5. Yoshua Bengio
6. Alex Krizhevsky
7. Sepp Hochreiter
8. Christian Szegedy
9. Yann LeCun
10. David E. Rumelhart

Papers from Yudong Cao's perspective

Ordered by how strongly the researchers Yudong Cao 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
3. Long Short-Term Memory
4. Attention is All you Need (Neural Information Processing Systems)
5. ImageNet classification with deep convolutional neural networks
6. Gradient-based learning applied to document recognition
7. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
9. ImageNet: A large-scale hierarchical image database
10. Dropout: a simple way to prevent neural networks from overfitting

Their papers

• A novel time–frequency Transformer based on self–attention mechanism and its application in fault diagnosis of rolling bearings (2021) — 447 citations
• A novel temporal convolutional network with residual self-attention mechanism for remaining useful life prediction of rolling bearings (2021) — 332 citations