Feicheng Wang

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 10 citations into it

Whom Feicheng Wang trusts overall

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

1. Matus Telgarsky
2. Dmitry Yarotsky
3. Kaiming He

Who trusts Feicheng Wang overall

1. Patrick Kidger
2. Hongzhou Lin

Papers from Feicheng Wang's perspective

Ordered by how strongly the researchers Feicheng 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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Learning Multiple Layers of Features from Tiny Images
6. Multilayer feedforward networks are universal approximators
7. On the Expressive Power of Deep Learning: A Tensor Analysis
8. Long Short-Term Memory
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Benefits of Depth in Neural Networks

Their papers

• The Expressive Power of Neural Networks: A View from the Width (2017) — 1,013 citations