Daniel Neil

Artificial Intelligence · 2013–2020

A researcher in the Science corpus: 8 papers; trusts 64 researchers and is trusted by 29 researchers here, as inferred from the citation graph.

Subfields

Whom Daniel Neil trusts overall

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

  1. Geoffrey E. Hinton
  2. Yann LeCun
  3. Diederik P. Kingma
  4. Yoshua Bengio
  5. Alex Graves
  6. Shih-Chii Liu
  7. Kyunghyun Cho
  8. J. Urgen Schmidhuber
  9. Jimmy Ba
  10. Alex Krizhevsky

Who trusts Daniel Neil overall

  1. Michael Pfeiffer
  2. Peter U. Diehl
  3. Shih-Chii Liu
  4. Giacomo Indiveri
  5. Ioana Bica
  6. Amos Sironi
  7. Hesham Mostafa
  8. Matthew Cook
  9. Guillermo Gallego
  10. Thomas Pfeil

Papers from Daniel Neil's perspective

Ordered by how strongly the researchers Daniel Neil 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. 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