John Salvatier

Artificial Intelligence · 2016–2020

A researcher in the Science corpus: 6 papers; trusts 22 researchers and is trusted by 30 researchers here, as inferred from the citation graph.

Subfields

Whom John Salvatier trusts overall

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

  1. Matthew D. Hoffman
  2. Thomas G. Dietterich
  3. David J. Spiegelhalter
  4. Richard S. Sutton
  5. W. B. Knox
  6. Andrew Gelman
  7. Andrew Y. Ng
  8. Javier García
  9. Lihong Li
  10. Peter Stone

Who trusts John Salvatier overall

  1. Andreas Holzinger
  2. Willie Neiswanger
  3. Garrett Bernstein
  4. Adarsh Subbaswamy
  5. Dustin Tran
  6. Aki Vehtari
  7. Sebastian Raschka
  8. Du Phan
  9. Hui Yie Teh
  10. Andrew Gelman

Papers from John Salvatier's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Reinforcement Learning: An Introduction
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. Long Short-Term Memory
  7. Going deeper with convolutions
  8. Attention is All you Need (Neural Information Processing Systems)
  9. ImageNet: A large-scale hierarchical image database
  10. Learning Multiple Layers of Features from Tiny Images

Their papers