Jonathan W. Siegel

2019

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 1 researcher here, as inferred from the citation graph.

Whom Jonathan W. Siegel trusts overall

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

  1. Yuly Makovoz
  2. Allan Pinkus
  3. Kurt Hornik
  4. Andrew R. Barron
  5. Dmitry Yarotsky
  6. Robert S. Strichartz
  7. Vinod Nair
  8. Geoffrey E. Hinton
  9. Yann LeCun
  10. Yoshua Bengio

Who trusts Jonathan W. Siegel overall

  1. Shuhao Cao

Papers from Jonathan W. Siegel's perspective

Ordered by how strongly the researchers Jonathan W. Siegel trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Rectified Linear Units Improve Restricted Boltzmann Machines
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Learning Multiple Layers of Features from Tiny Images
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet: A large-scale hierarchical image database
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers