Jordan Hoffmann

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 7 papers; trusts 87 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Jordan Hoffmann trusts overall

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

  1. Diederik P. Kingma
  2. Yoshua Bengio
  3. Geoffrey E. Hinton
  4. Alex Krizhevsky
  5. Ilya Sutskever
  6. Yann LeCun
  7. Jimmy Ba
  8. Alex Graves
  9. J. Urgen Schmidhuber
  10. Tomas Mikolov

Who trusts Jordan Hoffmann overall

  1. William L. Hamilton
  2. Wayne Xin Zhao
  3. Q. Liao
  4. Yi Tay
  5. Xiao Liu
  6. Jason Wei
  7. Antonia Creswell
  8. Niklas Muennighoff
  9. Mengzhou Xia
  10. Bernhard Schölkopf

Papers from Jordan Hoffmann's perspective

Ordered by how strongly the researchers Jordan Hoffmann 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. Attention is All you Need (Neural Information Processing Systems)
  5. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Learning Multiple Layers of Features from Tiny Images
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers