Jieyu Lin

Reinforcement Learning · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 33 researchers and is trusted by 8 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 37 citations into it; #1,373 of 2,242 by trust here, #2,125 by citations
• Artificial Intelligence — 33 citations into it; #19,078 of 35,345 by trust here, #31,361 by citations
• Electrical and Electronic Engineering — 6 citations into it
• Game & Decision Theory — 6 citations into it
• Computational Theory and Mathematics — 5 citations into it
• Computer Science Applications — 5 citations into it

Whom Jieyu Lin trusts overall

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

1. Jakob N. Foerster
2. Tabish Rashid
3. Mikayel Samvelyan
4. Daewoo Kim
5. Gregory Farquhar
6. Ming Tan
7. Richard S. Sutton
8. Christian Schröder de Witt
9. Frans Adriaan Oliehoek
10. Geoffrey E. Hinton

Who trusts Jieyu Lin overall

1. Tabish Rashid

Papers from Jieyu Lin's perspective

Ordered by how strongly the researchers Jieyu Lin 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. Long Short-Term Memory
4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. Reinforcement Learning: An Introduction
8. ImageNet: A large-scale hierarchical image database
9. Asynchronous Methods for Deep Reinforcement Learning
10. Human-level control through deep reinforcement learning

Their papers

• Succinct and Robust Multi-Agent Communication With Temporal Message Control (2020) — 84 citations
• Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control (2019) — 134 citations