Jacqueline Yau

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 89 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jacqueline Yau trusts overall

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

  1. Alex Krizhevsky
  2. Kaiming He
  3. Geoffrey E. Hinton
  4. Ross B. Girshick
  5. Shaoqing Ren
  6. Jia Deng
  7. Ilya Sutskever
  8. Yoshua Bengio
  9. Yann LeCun
  10. Diederik P. Kingma

Who trusts Jacqueline Yau overall

  1. Abeba Birhane

Papers from Jacqueline Yau's perspective

Ordered by how strongly the researchers Jacqueline Yau 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. ImageNet: A large-scale hierarchical image database
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. Learning Multiple Layers of Features from Tiny Images
  7. ImageNet Large Scale Visual Recognition Challenge
  8. Long Short-Term Memory
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers