Xin Wang

Artificial Intelligence · with Chang · 2020

A researcher in the Science corpus: 2 papers; trusts 346 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 185 citations into it
• Computer Vision and Pattern Recognition — 168 citations into it
• Neural Architecture Search & AutoML — 49 citations into it
• Model Architectures — 40 citations into it
• Optimization & Training — 26 citations into it
• Evaluation & Benchmarks — 22 citations into it
• Probabilistic & Bayesian Methods — 16 citations into it
• Representation & Self-Supervised Learning — 8 citations into it

Whom Xin Wang trusts overall

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

1. Geoffrey E. Hinton
2. Alex Krizhevsky
3. Kaiming He
4. Diederik P. Kingma
5. Yoshua Bengio
6. Yann LeCun
7. Karen Simonyan
8. Ilya Sutskever
9. Ross B. Girshick
10. Quoc V. Le

Papers from Xin Wang's perspective

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

Their papers

• A Comprehensive Survey of Neural Architecture Search (2020) — 868 citations
• A Survey of Deep Active Learning (2020) — 1,521 citations