Tina Jiang

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 16 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 27 citations into it
• Reinforcement Learning — 21 citations into it
• Game & Decision Theory — 10 citations into it
• Management Science and Operations Research — 10 citations into it
• Economics and Econometrics — 7 citations into it

Whom Tina Jiang trusts overall

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

1. Rémi Coulom
2. Volodymyr Mnih
3. Yuandong Tian
4. David Silver
5. Jakob N. Foerster
6. Neil Burch
7. Martin A. Zinkevich

Papers from Tina Jiang's perspective

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

1. Asynchronous Methods for Deep Reinforcement Learning
2. Mastering the game of Go with deep neural networks and tree search
3. Playing Atari with Deep Reinforcement Learning (arXiv.org)
4. ImageNet classification with deep convolutional neural networks
5. Gradient-based learning applied to document recognition
6. Mastering the game of Go without human knowledge
7. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
8. Long Short-Term Memory
9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
10. Attention is All you Need (Neural Information Processing Systems)

Their papers

• Joint Policy Search for Multi-agent Collaboration with Imperfect Information (2020) — 24 citations