Jan Gerretzen

Artificial Intelligence · 2013–2017

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

Subfields

Whom Jan Gerretzen trusts overall

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

  1. L. Eon Bottou
  2. Yoshua Bengio
  3. Yann LeCun
  4. Alex Krizhevsky
  5. Xavier Glorot
  6. Geoffrey E. Hinton
  7. Trevor J. Hastie
  8. James Bergstra

Papers from Jan Gerretzen's perspective

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

Their papers