Quentin Rebjock

Optimization & Training · 2019

A researcher in the Science corpus: 1 paper; trusts 23 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

Whom Quentin Rebjock trusts overall

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

  1. Alex Krizhevsky
  2. Kaiming He
  3. Karen Simonyan
  4. Geoffrey E. Hinton
  5. Diederik P. Kingma
  6. X. Zhang
  7. Yoshua Bengio
  8. Yann LeCun
  9. Andrew Zisserman
  10. Shaoqing Ren

Who trusts Quentin Rebjock overall

  1. Sai Praneeth Karimireddy
  2. Sebastian U. Stich
  3. Tao Lin
  4. Cong Xie
  5. Shuai Zheng
  6. Constantin Philippenko
  7. Martin Jaggi
  8. Thijs Vogels
  9. Felix Sattler
  10. Mingzhe Chen

Papers from Quentin Rebjock's perspective

Ordered by how strongly the researchers Quentin Rebjock 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. Learning Multiple Layers of Features from Tiny Images
  5. Gradient-based learning applied to document recognition
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers