Jingchang Liu

Optimization & Training · 2019

A researcher in the Science corpus: 1 paper; trusts 9 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Jingchang Liu trusts overall

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

  1. Yann LeCun
  2. Sebastian U. Stich
  3. Christian Szegedy
  4. Sergey Ioffe
  5. Hao Yu
  6. Yoon Kim
  7. Geoffrey E. Hinton
  8. Alex Krizhevsky
  9. Hang Su
  10. Yoshua Bengio

Who trusts Jingchang Liu overall

  1. Farzin Haddadpour

Papers from Jingchang Liu's perspective

Ordered by how strongly the researchers Jingchang 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. ImageNet: A large-scale hierarchical image database
  4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  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. Learning Multiple Layers of Features from Tiny Images
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers