Sheng-De Wang

Computer Vision and Pattern Recognition · with Chiu · 2017

A researcher in the Science corpus: 2 papers; trusts 161 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Computer Vision and Pattern Recognition — 48 citations into it
• Generative Models — 34 citations into it
• Artificial Intelligence — 32 citations into it
• Representation & Self-Supervised Learning — 24 citations into it

Whom Sheng-De Wang trusts overall

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

1. Diederik P. Kingma
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Alex Krizhevsky
5. Karen Simonyan
6. Kaiming He
7. Max Welling
8. Yann LeCun
9. Ilya Sutskever
10. Andrew Zisserman

Papers from Sheng-De Wang's perspective

Ordered by how strongly the researchers Sheng-De Wang 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. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. ImageNet: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Detach and Adapt: Learning Cross-Domain Disentangled Deep Representation (2017) — 117 citations
• Learning Cross-Domain Disentangled Deep Representation with Supervision from A Single Domain (2017) — 10 citations