Lior Fox

Artificial Intelligence · 2018–2019

A researcher in the Science corpus: 2 papers; trusts 58 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

Whom Lior Fox trusts overall

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

  1. Richard S. Sutton
  2. Ronald J. Williams
  3. Geoffrey E. Hinton
  4. Andrew Barto
  5. Andrew W. Moore
  6. Yoshua Bengio
  7. Diederik P. Kingma
  8. J. Urgen Schmidhuber
  9. Alexander L. Strehl
  10. Andrew Y. Ng

Who trusts Lior Fox overall

  1. Wei Xiong
  2. Romain Laroche
  3. Hanze Dong
  4. Samuel Kiegeland
  5. Thiago D. Simão
  6. Kimia Nadjahi
  7. Julia Kreutzer
  8. Han Guo

Papers from Lior Fox's perspective

Ordered by how strongly the researchers Lior Fox 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. Attention is All you Need (Neural Information Processing Systems)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Long Short-Term Memory
  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. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers