Deheng Ye

Artificial Intelligence · 4 papers · 2019–2023

A researcher in the Science corpus: 4 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 83 citations into it
• Reinforcement Learning — 62 citations into it

Whom Deheng Ye trusts overall

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

1. John Schulman
2. Diederik P. Kingma
3. Geoffrey E. Hinton
4. David Silver
5. Richard S. Sutton
6. Jimmy Ba
7. Yoshua Bengio
8. Volodymyr Mnih
9. Alex Krizhevsky
10. Oriol Vinyals

Who trusts Deheng Ye overall

1. Shengyi Huang
2. Shiyu Huang

Papers from Deheng Ye's perspective

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

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. Attention is All you Need (Neural Information Processing Systems)
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. ImageNet classification with deep convolutional neural networks
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• TiKick: Towards Playing Multi-agent Football Full Games from Single-agent Demonstrations (2021) — 30 citations
• Mastering Complex Control in MOBA Games with Deep Reinforcement Learning (2019) — 410 citations
• Supervised Learning Achieves Human-Level Performance in MOBA Games: A Case Study of Honor of Kings (2020) — 60 citations
• RLTF: Reinforcement Learning from Unit Test Feedback (2023) — 134 citations