Fan Feng

Artificial Intelligence · with Huang · 2021

A researcher in the Science corpus: 1 paper; trusts 32 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 45 citations into it
• Reinforcement Learning — 26 citations into it
• Computer Vision and Pattern Recognition — 8 citations into it
• Probabilistic & Bayesian Methods — 6 citations into it
• Causal Inference & Discovery — 5 citations into it

Whom Fan Feng trusts overall

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

1. Richard S. Sutton
2. Geoffrey E. Hinton
3. Diederik P. Kingma
4. Sergey Levine
5. Yoshua Bengio
6. John Schulman
7. J. Urgen Schmidhuber
8. Sepp Hochreiter
9. Volodymyr Mnih
10. Chelsea Finn

Papers from Fan Feng's perspective

Ordered by how strongly the researchers Fan 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
4. Long Short-Term Memory
5. Gradient-based learning applied to document recognition
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. Learning Multiple Layers of Features from Tiny Images
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Reinforcement Learning: An Introduction

Their papers

• AdaRL: What, Where, and How to Adapt in Transfer Reinforcement Learning (2021) — 77 citations