Ou Jin

Artificial Intelligence · 2010–2012

A researcher in the Science corpus: 2 papers; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ou Jin trusts overall

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

  1. David G. Lowe
  2. Frederick Jelinek
  3. Ellen Riloff
  4. Hal Daumé Iii
  5. Jon M. Kleinberg
  6. Bo Pang
  7. Jing Jiang
  8. Minqing Hu
  9. Rie Kubota Ando

Papers from Ou Jin's perspective

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

Their papers