Daniel Hewlett

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 3 papers; trusts 92 researchers and is trusted by 5 researchers here, as inferred from the citation graph.

Subfields

Whom Daniel Hewlett trusts overall

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

  1. Alex Graves
  2. Ilya Sutskever
  3. Yoshua Bengio
  4. Diederik P. Kingma
  5. Geoffrey E. Hinton
  6. Kyunghyun Cho
  7. Yann LeCun
  8. Sepp Hochreiter
  9. Oriol Vinyals
  10. Dzmitry Bahdanau

Who trusts Daniel Hewlett overall

  1. Johannes Welbl
  2. Shuohang Wang
  3. Minjoon Seo
  4. Matt Gardner
  5. Eunsol Choi
  6. Christopher Clark
  7. Simon Suster
  8. Jianfeng Gao
  9. Ondrej Bajgar
  10. Tom Kenter

Papers from Daniel Hewlett's perspective

Ordered by how strongly the researchers Daniel Hewlett 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. 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. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  10. Learning Multiple Layers of Features from Tiny Images

Their papers