Nathan Siegle Hartmann

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Nathan Siegle Hartmann trusts overall

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

  1. Tomas Mikolov
  2. Yoshua Bengio
  3. Armand Joulin
  4. Ronan Collobert
  5. Piotr Bojanowski
  6. Jeffrey Pennington
  7. Geoffrey E. Hinton
  8. Richard Socher
  9. Marco Baroni
  10. Yann LeCun

Who trusts Nathan Siegle Hartmann overall

  1. Brenda Salenave Santana
  2. Edouard Grave
  3. Vinicius Woloszyn

Papers from Nathan Siegle Hartmann's perspective

Ordered by how strongly the researchers Nathan Siegle Hartmann 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. Attention is All you Need (Neural Information Processing Systems)
  4. Long Short-Term Memory
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers