John Thickstun

Artificial Intelligence · 2017–2023

A researcher in the Science corpus: 6 papers; trusts 236 researchers and is trusted by 13 researchers here, as inferred from the citation graph.

Subfields

Whom John Thickstun trusts overall

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

  1. Alex Krizhevsky
  2. Diederik P. Kingma
  3. Geoffrey E. Hinton
  4. Yoshua Bengio
  5. Radford M. Neal
  6. Ilya Sutskever
  7. Max Welling
  8. Yann LeCun
  9. Aäron van den Oord
  10. Kaiming He

Who trusts John Thickstun overall

  1. Sachin Kumar
  2. Aaron Lou
  3. Karan Goel
  4. Baizhou Huang
  5. Sander Dieleman
  6. Hyung-Seok Oh
  7. Jiacheng Ye
  8. Biswajit Paria
  9. Akim Kotelnikov

Papers from John Thickstun's perspective

Ordered by how strongly the researchers John Thickstun 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. 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. Learning Multiple Layers of Features from Tiny Images
  9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers