Richard Tucker

Computer Vision and Pattern Recognition · 2018–2020

A researcher in the Science corpus: 6 papers; trusts 481 researchers and is trusted by 75 researchers here, as inferred from the citation graph.

Subfields

Whom Richard Tucker trusts overall

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

  1. Diederik P. Kingma
  2. Jimmy Ba
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Kaiming He
  6. Zhengqi Li
  7. Karen Simonyan
  8. Yoshua Bengio
  9. Ross B. Girshick
  10. Yann LeCun

Who trusts Richard Tucker overall

  1. Cheng Sun
  2. Zhengqi Li
  3. Chen-Hsuan Lin
  4. Jonah Philion
  5. Stephen Lombardi
  6. Suttisak Wizadwongsa
  7. Ben Mildenhall
  8. Eric Chan
  9. Min Sun
  10. Noah Snavely

Papers from Richard Tucker's perspective

Ordered by how strongly the researchers Richard Tucker 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. ImageNet: A large-scale hierarchical image database
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Long Short-Term Memory
  9. Going deeper with convolutions
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers