Jeffrey S. Seely

Artificial Intelligence · 2018–2021

A researcher in the Science corpus: 2 papers; trusts 24 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Jeffrey S. Seely trusts overall

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

  1. Kaiming He
  2. Geoffrey E. Hinton
  3. Alex Krizhevsky
  4. Yoshua Bengio
  5. Diederik P. Kingma
  6. Yann LeCun
  7. Antonio Torralba
  8. David Lopez-Paz
  9. Ilya Sutskever
  10. Arthur Gretton

Papers from Jeffrey S. Seely's perspective

Ordered by how strongly the researchers Jeffrey S. Seely 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. Gradient-based learning applied to document recognition
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  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. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers