Ye Wang

Computer Vision and Pattern Recognition · with Cheng · 2021

A researcher in the Science corpus: 1 paper; trusts 29 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ye Wang trusts overall

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

  1. Diederik P. Kingma
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Sergey Ioffe
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Dekang Lin
  8. Christian Szegedy
  9. Jimmy Ba
  10. Yann LeCun

Papers from Ye Wang's perspective

Ordered by how strongly the researchers Ye 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. ImageNet classification with deep convolutional neural networks
  4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Long Short-Term Memory
  8. ImageNet: A large-scale hierarchical image database
  9. Et al
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers