Scott Sievert

Artificial Intelligence · 2015–2020

A researcher in the Science corpus: 4 papers; trusts 9 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Scott Sievert trusts overall

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

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

Who trusts Scott Sievert overall

  1. Konstantin Mishchenko
  2. Sai Praneeth Karimireddy
  3. Mohammad Mohammadi Amiri
  4. Jiawei Zhao
  5. Filip Hanzely
  6. Thijs Vogels

Papers from Scott Sievert's perspective

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

Their papers