Yao-Min Feng

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 18 citations into it
• Reinforcement Learning — 12 citations into it

Whom Yao-Min Feng trusts overall

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

1. John Schulman
2. Anirudh Goyal
3. Geoffrey E. Hinton
4. Yoshua Bengio
5. Sergey Levine
6. Diederik P. Kingma

Papers from Yao-Min Feng's perspective

Ordered by how strongly the researchers Yao-Min Feng 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. Proximal Policy Optimization Algorithms (arXiv.org)
8. This PDF file includes: Materials and Methods
9. ImageNet: A large-scale hierarchical image database
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Toward Robust Long Range Policy Transfer (2021) — 8 citations