Changxi Zhu

Artificial Intelligence · 2019–2022

A researcher in the Science corpus: 3 papers; trusts 13 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 69 citations into it
• Reinforcement Learning — 53 citations into it
• Game & Decision Theory — 11 citations into it

Whom Changxi Zhu trusts overall

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

1. Richard S. Sutton
2. Ming Tan
3. Christopher J. C. H. Watkins
4. Andrew Barto
5. Caroline Claus
6. Geoffrey E. Hinton
7. Tabish Rashid
8. Peter S. Dayan
9. Mikayel Samvelyan
10. Laëtitia Matignon

Papers from Changxi Zhu's perspective

Ordered by how strongly the researchers Changxi Zhu 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. Attention is All you Need (Neural Information Processing Systems)
6. Gradient-based learning applied to document recognition
7. Human-level control through deep reinforcement learning
8. ImageNet: A large-scale hierarchical image database
9. Reinforcement Learning: An Introduction
10. GENERATIVE ADVERSARIAL NETS

Their papers

• A survey of multi-agent deep reinforcement learning with communication (2022) — 310 citations
• A Q-values Sharing Framework for Multi-agent Reinforcement Learning under Budget Constraint (2020) — 10 citations
• A Q-values Sharing Framework for Multiple Independent Q-learners (2019) — 12 citations