Lorna Ashton

Artificial Intelligence · 2016–2017

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 Lorna Ashton trusts overall

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

  1. Andrew L. Maas
  2. Diederik P. Kingma
  3. Christian Szegedy
  4. Sergey Ioffe
  5. Kaiming He
  6. Geoffrey E. Hinton

Papers from Lorna Ashton's perspective

Ordered by how strongly the researchers Lorna Ashton 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Going deeper with convolutions
  4. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  5. Dropout: a simple way to prevent neural networks from overfitting
  6. ImageNet classification with deep convolutional neural networks
  7. Gradient-based learning applied to document recognition
  8. Long Short-Term Memory
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers