David J. Nott

Artificial Intelligence · with Tan · 2000–2016

A researcher in the Science corpus: 7 papers; trusts 113 researchers and is trusted by 49 researchers here, as inferred from the citation graph.

Subfields

Whom David J. Nott trusts overall

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

  1. Michael I. Jordan
  2. Radford M. Neal
  3. Matt P. Wand
  4. David M. Blei
  5. Tim Hesterberg
  6. Zoubin Ghahramani
  7. Matthew D. Hoffman
  8. D. M. Titterington
  9. Geoffrey E. Hinton
  10. Charles M. Bishop

Who trusts David J. Nott overall

  1. Linda S. L. Tan
  2. Andreas Krause
  3. Chandra R. Bhat
  4. Tim Salimans
  5. Carlos Guestrin
  6. David M. Blei
  7. Michael L. Stein
  8. Ming Xu
  9. George Papamakarios
  10. Yanan Fan

Papers from David J. Nott's perspective

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

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

Their papers