Daisy Stanton

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 9 papers; trusts 79 researchers and is trusted by 83 researchers here, as inferred from the citation graph.

Subfields

Whom Daisy Stanton trusts overall

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

  1. Diederik P. Kingma
  2. Alex Graves
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Kyunghyun Cho
  6. Jimmy Ba
  7. Ilya Sutskever
  8. Dzmitry Bahdanau
  9. Oriol Vinyals
  10. R. Skerry-Ryan

Who trusts Daisy Stanton overall

  1. Xu Tan
  2. Rui Liu
  3. Shan Yang
  4. Yi Ren
  5. Eric Battenberg
  6. Frank K. Soong
  7. Yinjiao Lei
  8. Sang-Hoon Lee
  9. Lei Xie
  10. Younggun Lee

Papers from Daisy Stanton's perspective

Ordered by how strongly the researchers Daisy Stanton 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. Long Short-Term Memory
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers