Yun Lin

Artificial Intelligence · with Chen · 2017–2020

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

Subfields

Whom Yun Lin trusts overall

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

  1. Tim O'Shea
  2. Alex Krizhevsky
  3. Augustus Odena
  4. Fan Meng
  5. Geoffrey E. Hinton
  6. Ilya Sutskever
  7. Jakob Hoydis
  8. Jost Tobias Springenberg
  9. Li Fei-Fei
  10. Chris Olah

Papers from Yun Lin's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Gradient-based learning applied to document recognition
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Long Short-Term Memory
  6. Going deeper with convolutions
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Learning Multiple Layers of Features from Tiny Images
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet: A large-scale hierarchical image database

Their papers