Elizabeth Sieber

Artificial Intelligence · 2023

A researcher in the Science corpus: 1 paper; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Elizabeth Sieber trusts overall

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

  1. Chin-Yew Lin

Papers from Elizabeth Sieber's perspective

Ordered by how strongly the researchers Elizabeth Sieber trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  2. Attention is All you Need (Neural Information Processing Systems)
  3. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)
  4. Long Short-Term Memory
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  7. ImageNet classification with deep convolutional neural networks
  8. ROUGE: A Package for Automatic Evaluation of Summaries
  9. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  10. Gradient-based learning applied to document recognition

Their papers