Sha Yang

Computer Vision and Pattern Recognition · with Kanazawa · 2021

A researcher in the Science corpus: 1 paper; trusts 33 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 34 citations into it; #16,942 of 21,575 by trust here, #15,529 by citations
• Artificial Intelligence — 14 citations into it
• Control and Systems Engineering — 13 citations into it; #6,315 of 8,257 by trust here, #4,262 by citations

Whom Sha Yang trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Jimmy Ba
4. Yoshua Bengio
5. Alex Krizhevsky
6. Jacob Devlin
7. Kaiming He
8. Ilya Sutskever
9. Yann LeCun
10. Mykhaylo Andriluka

Who trusts Sha Yang overall

1. Mathis Petrovich
2. Guy Tevet
3. Jo-Han Tseng
4. Ye Yuan
5. Shao-Wei Liu

Papers from Sha Yang's perspective

Ordered by how strongly the researchers Sha Yang 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. ImageNet: A large-scale hierarchical image database
7. Gradient-based learning applied to document recognition
8. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Going deeper with convolutions

Their papers

• AI Choreographer: Music Conditioned 3D Dance Generation with AIST++ (2021) — 734 citations