Jonathan Weber

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 50 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Jonathan Weber trusts overall

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

  1. Yoshua Bengio
  2. Yann LeCun
  3. Geoffrey E. Hinton
  4. Diederik P. Kingma
  5. Kaiming He
  6. Alex Krizhevsky
  7. Radford M. Neal
  8. Ilya Sutskever
  9. Christian Szegedy
  10. Anthony J. Bagnall

Who trusts Jonathan Weber overall

  1. Angus Dempster

Papers from Jonathan Weber's perspective

Ordered by how strongly the researchers Jonathan Weber 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. Attention is All you Need (Neural Information Processing Systems)
  5. Gradient-based learning applied to document recognition
  6. Long Short-Term Memory
  7. Going deeper with convolutions
  8. ImageNet: A large-scale hierarchical image database
  9. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers