William Agnew

Artificial Intelligence · 2021–2023

A researcher in the Science corpus: 4 papers; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom William Agnew trusts overall

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

  1. Geoffrey E. Hinton
  2. Yoshua Bengio
  3. Diederik P. Kingma
  4. Alex Krizhevsky
  5. Ilya Sutskever
  6. Yann LeCun
  7. Kaiming He
  8. Ruslan Salakhutdinov
  9. Jacob Devlin
  10. Alex Graves

Papers from William Agnew's perspective

Ordered by how strongly the researchers William Agnew 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. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  8. Gradient-based learning applied to document recognition
  9. Learning Multiple Layers of Features from Tiny Images
  10. ImageNet Large Scale Visual Recognition Challenge

Their papers