Julius Hannink

Artificial Intelligence · 2017

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Julius Hannink trusts overall

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

  1. Geoffrey E. Hinton
  2. Radford M. Neal
  3. L. Eon Bottou
  4. Leo Breiman
  5. David D. Lewis
  6. John Scott Bridle
  7. Pedro M. Domingos
  8. Yann LeCun

Papers from Julius Hannink's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. ImageNet classification with deep convolutional neural networks
  3. Gradient-based learning applied to document recognition
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Learning Multiple Layers of Features from Tiny Images
  8. ImageNet: A large-scale hierarchical image database
  9. Improving neural networks by preventing co-adaptation of feature detectors
  10. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification

Their papers