Shengyu Feng

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 23 citations into it
• Reinforcement Learning — 21 citations into it

Whom Shengyu Feng trusts overall

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

1. Aviral Kumar
2. Sergey Levine
3. John Schulman
4. Richard S. Sutton
5. Scott Fujimoto
6. Geoffrey E. Hinton
7. Marc G. Bellemare
8. George Tucker
9. Diederik P. Kingma
10. Tuomas Haarnoja

Who trusts Shengyu Feng overall

1. Scott Fujimoto

Papers from Shengyu Feng's perspective

Ordered by how strongly the researchers Shengyu Feng 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. ImageNet classification with deep convolutional neural networks
3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Gradient-based learning applied to document recognition
5. Attention is All you Need (Neural Information Processing Systems)
6. Long Short-Term Memory
7. Trust Region Policy Optimization (International Conference on Machine Learning)
8. Reinforcement Learning: An Introduction
9. ImageNet: A large-scale hierarchical image database
10. Proximal Policy Optimization Algorithms (arXiv.org)

Their papers

• Batch Reinforcement Learning Through Continuation Method (2021) — 16 citations