Jun Yan

Control and Systems Engineering · with He · 2016–2019

A researcher in the Science corpus: 2 papers; trusts 10 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jun Yan trusts overall

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

  1. Geoffrey E. Hinton
  2. Madalena Costa
  3. Diederik P. Kingma
  4. Vinod Nair
  5. L. V. D. van der Maaten
  6. Zhicheng Cui

Papers from Jun Yan's perspective

Ordered by how strongly the researchers Jun Yan trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. Dropout: a simple way to prevent neural networks from overfitting
  3. ImageNet classification with deep convolutional neural networks
  4. Rectified Linear Units Improve Restricted Boltzmann Machines
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Gradient-based learning applied to document recognition
  7. Deep Learning
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Long Short-Term Memory
  10. Learning Multiple Layers of Features from Tiny Images

Their papers