Tom Diethe

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 4 papers; trusts 45 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Tom Diethe trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Manfred Opper
  4. Cynthia Dwork
  5. Ryan P. Adams
  6. Hans Raj Tiwary
  7. Philippe Flajolet
  8. Yoshua Bengio
  9. L. Eon Bottou
  10. Radford M. Neal

Who trusts Tom Diethe overall

  1. Timothée Lesort
  2. K. J. Joseph
  3. Sayna Ebrahimi
  4. Zheda Mai
  5. Hexiang Hu
  6. Cuong V Nguyen

Papers from Tom Diethe's perspective

Ordered by how strongly the researchers Tom Diethe 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Learning Multiple Layers of Features from Tiny Images
  6. ImageNet: A large-scale hierarchical image database
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Long Short-Term Memory
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers