Eva L. Dyer

Artificial Intelligence · 2021

A researcher in the Science corpus: 2 papers; trusts 31 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Eva L. Dyer trusts overall

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

  1. Diederik P. Kingma
  2. Geoffrey E. Hinton
  3. Yoshua Bengio
  4. Kaiming He
  5. Jimmy Ba
  6. Alex Krizhevsky
  7. Sergey Ioffe
  8. Max Welling
  9. Thomas Kipf
  10. Yann LeCun

Papers from Eva L. Dyer's perspective

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

Their papers