Te-Yen Wu

Reinforcement Learning · 2022

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 Te-Yen Wu trusts

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

  1. Kyle Duffie (in Reinforcement Learning)
  2. Allen Newell (in Cognitive Science & Psychology)

Papers from Te-Yen Wu's perspective

Ordered by how strongly the researchers Te-Yen Wu trusts endorse each paper. Same corpus, a different order for every researcher.

  1. Language Models are Unsupervised Multitask Learners
  2. Language Models are Few-Shot Learners (Neural Information Processing Systems)
  3. Attention is All you Need (Neural Information Processing Systems)
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Exploring the Limits of Transfer Learning with a Unified Text-to-Text Transformer (Journal of machine learning research)
  6. ImageNet classification with deep convolutional neural networks
  7. Long Short-Term Memory
  8. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  9. Gradient-based learning applied to document recognition
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers