Lucas Liebenwein

Computer Vision and Pattern Recognition · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 120 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Lucas Liebenwein trusts overall

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

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

Who trusts Lucas Liebenwein overall

  1. Dan Feldman
  2. Ben Mussay
  3. Marwa El Halabi
  4. Yang He
  5. Mao Ye
  6. Suraj Srinivas
  7. Samson Zhou
  8. Lingao Xiao
  9. Margarita Osadchy

Papers from Lucas Liebenwein's perspective

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

Their papers