Jack Xin

Computer Vision and Pattern Recognition · 2015–2019

A researcher in the Science corpus: 2 papers; trusts 37 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jack Xin trusts overall

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

  1. E.J. Candes
  2. David L. Donoho
  3. Joel A. Tropp
  4. Alex Krizhevsky
  5. Tao Pham Dinh
  6. Yoshua Bengio
  7. Terence Tao
  8. Gitta Kutyniok
  9. Kaiming He
  10. Yann LeCun

Papers from Jack Xin's perspective

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

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

Their papers