Ying-Long Bai

Computer Vision and Pattern Recognition · 2021

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

Subfields

Whom Ying-Long Bai trusts overall

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

  1. Alex Krizhevsky
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Ilya Sutskever
  5. Ilya Loshchilov
  6. Yoshua Bengio
  7. Yann LeCun
  8. X. Zhang
  9. Diederik P. Kingma
  10. Shaoqing Ren

Papers from Ying-Long Bai's perspective

Ordered by how strongly the researchers Ying-Long Bai 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. Learning Multiple Layers of Features from Tiny Images
  4. ImageNet: A large-scale hierarchical image database
  5. Gradient-based learning applied to document recognition
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Long Short-Term Memory
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers