William Schuler

Artificial Intelligence · 2011–2020

A researcher in the Science corpus: 3 papers; trusts 65 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom William Schuler trusts overall

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

  1. Yoon Kim
  2. Kaiming He
  3. Alec Radford
  4. Daniel Klein
  5. Geoffrey E. Hinton
  6. Andrew Rosenberg
  7. Yoshua Bengio
  8. Tsung-Yi Lin
  9. Diederik P. Kingma
  10. Alex Krizhevsky

Papers from William Schuler's perspective

Ordered by how strongly the researchers William Schuler 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. Long Short-Term Memory
  6. Gradient-based learning applied to document recognition
  7. ImageNet: A large-scale hierarchical image database
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  10. Microsoft COCO: Common Objects in Context

Their papers