Kyle Gao

Computer Vision and Pattern Recognition · 2022

A researcher in the Science corpus: 1 paper; trusts 161 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Kyle Gao trusts overall

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

  1. Alex Krizhevsky
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Yoshua Bengio
  6. Ilya Sutskever
  7. Andreas Geiger
  8. Yann LeCun
  9. Ross B. Girshick
  10. Karen Simonyan

Papers from Kyle Gao's perspective

Ordered by how strongly the researchers Kyle Gao 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Attention is All you Need (Neural Information Processing Systems)
  5. ImageNet: A large-scale hierarchical image database
  6. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  7. Long Short-Term Memory
  8. Gradient-based learning applied to document recognition
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers