Aiping Liu

Computer Vision and Pattern Recognition · 2021–2022

A researcher in the Science corpus: 2 papers; trusts 302 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Aiping Liu trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Diederik P. Kingma
  4. Alex Krizhevsky
  5. Yoshua Bengio
  6. Ross B. Girshick
  7. Jimmy Ba
  8. Yann LeCun
  9. Ilya Sutskever
  10. Sergey Ioffe

Papers from Aiping Liu's perspective

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

Their papers