Tom Gunter

Artificial Intelligence · 2014–2015

A researcher in the Science corpus: 3 papers; trusts 13 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Tom Gunter trusts overall

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

  1. Carl E. Rasmussen
  2. Michalis K. Titsias
  3. Radford M. Neal
  4. Anthony OʼHagan
  5. Neil D. Lawrence
  6. Zoubin Ghahramani
  7. James Hensman
  8. Christopher K. I. Williams
  9. Michael A. Osborne
  10. Peter J. Diggle

Who trusts Tom Gunter overall

  1. Philipp Hennig
  2. Michael A. Osborne
  3. Chris M. Lloyd
  4. François‐Xavier Briol
  5. Chris J. Oates
  6. Mark A. Girolami
  7. James Hensman
  8. Pavel Izmailov
  9. Wenzhao Lian

Papers from Tom Gunter's perspective

Ordered by how strongly the researchers Tom Gunter 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. 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. Attention is All you Need (Neural Information Processing Systems)
  8. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
  9. ImageNet: A large-scale hierarchical image database
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers