Neale Ratzlaff

Artificial Intelligence · 2019

A researcher in the Science corpus: 1 paper; trusts 50 researchers and is trusted by 4 researchers here, as inferred from the citation graph.

Subfields

Whom Neale Ratzlaff trusts overall

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

  1. Geoffrey E. Hinton
  2. Ian J. Goodfellow
  3. Alex Krizhevsky
  4. Diederik P. Kingma
  5. Yoshua Bengio
  6. Yann LeCun
  7. Max Welling
  8. Yarin Gal
  9. Karen Simonyan
  10. Christian Szegedy

Who trusts Neale Ratzlaff overall

  1. Boris Knyazev
  2. Jie Gui
  3. Michal Drozdzal
  4. Zhenan Sun
  5. Graham W. Taylor

Papers from Neale Ratzlaff's perspective

Ordered by how strongly the researchers Neale Ratzlaff 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. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers