Charlie Nash

Artificial Intelligence · 2018–2022

A researcher in the Science corpus: 10 papers; trusts 824 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

Whom Charlie Nash trusts overall

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

  1. Diederik P. Kingma
  2. Aäron van den Oord
  3. Geoffrey E. Hinton
  4. Kaiming He
  5. Alex Krizhevsky
  6. Yoshua Bengio
  7. Oriol Vinyals
  8. Ilya Sutskever
  9. Danilo Jimenez Rezende
  10. Alex Graves

Who trusts Charlie Nash overall

  1. Robin Rombach
  2. Xingguang Yan
  3. Patrick Esser
  4. Conor Durkan
  5. Sjoerd van Steenkiste
  6. Prafulla Dhariwal
  7. Jyoti Aneja
  8. Troy Luhman
  9. Emmanuel Bengio
  10. Rasool Fakoor

Papers from Charlie Nash's perspective

Ordered by how strongly the researchers Charlie Nash 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. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. ImageNet: A large-scale hierarchical image database
  7. Gradient-based learning applied to document recognition
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. ImageNet Large Scale Visual Recognition Challenge
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers