Yeh

Reinforcement Learning · 2019

A researcher in the Science corpus: 1 paper; trusts 33 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 20 citations into it
• Artificial Intelligence — 13 citations into it
• Cognitive Neuroscience — 7 citations into it
• Control and Systems Engineering — 5 citations into it
• Developmental and Educational Psychology — 5 citations into it

Whom Yeh trusts overall

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

1. Stephen W. Carden
2. L. R. Squire
3. R. Weinberg
4. Christopher J. C. H. Watkins
5. Geoffrey G. Towell
6. Pierre-Luc Bacon
7. Volodymyr Mnih
8. Tejas D. Kulkarni
9. Matthew Johnson
10. David Abel

Papers from Yeh's perspective

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

1. ImageNet classification with deep convolutional neural networks
2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Playing Atari with Deep Reinforcement Learning (arXiv.org)
7. Attention is All you Need (Neural Information Processing Systems)
8. Reinforcement Learning: An Introduction
9. ImageNet: A large-scale hierarchical image database
10. GENERATIVE ADVERSARIAL NETS

Their papers

• Bridging the Gap: Converting Human Advice into Imagined Examples (2019)