Yongchuan Tang

Computer Vision and Pattern Recognition · 2021

A researcher in the Science corpus: 1 paper; trusts 113 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 26 citations into it
• Generative Models — 17 citations into it
• Artificial Intelligence — 9 citations into it
• Optimization & Training — 7 citations into it
• Model Architectures — 6 citations into it

Whom Yongchuan Tang trusts overall

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

1. Kaiming He
2. Alex Krizhevsky
3. Diederik P. Kingma
4. Geoffrey E. Hinton
5. Tianfu Wu
6. Yoshua Bengio
7. Ross B. Girshick
8. Sergey Ioffe
9. Ilya Sutskever
10. Christian Szegedy

Papers from Yongchuan Tang's perspective

Ordered by how strongly the researchers Yongchuan Tang 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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
5. Gradient-based learning applied to document recognition
6. GENERATIVE ADVERSARIAL NETS
7. Attention is All you Need (Neural Information Processing Systems)
8. Long Short-Term Memory
9. ImageNet: A large-scale hierarchical image database
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Image Synthesis from Layout with Locality-Aware Mask Adaption (2021) — 89 citations