Shengyi Huang

Reinforcement Learning · 2020–2022

A researcher in the Science corpus: 2 papers; trusts 12 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 28 citations into it; #1,811 of 2,242 by trust here, #2,160 by citations
• Artificial Intelligence — 21 citations into it; #26,963 of 35,345 by trust here, #32,362 by citations

Whom Shengyi Huang trusts overall

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

1. John Schulman
2. Vinod Nair
3. Geoffrey E. Hinton
4. Richard S. Sutton
5. E. Todorov
6. Volodymyr Mnih
7. Marc G. Bellemare
8. Greg Brockman
9. Diederik P. Kingma
10. Scott Fujimoto

Who trusts Shengyi Huang overall

1. Rajkumar Ramamurthy
2. Rousslan Fernand Julien Dossa
3. Prithviraj Ammanabrolu
4. Chang Ye

Papers from Shengyi Huang's perspective

Ordered by how strongly the researchers Shengyi Huang 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
8. ImageNet: A large-scale hierarchical image database
9. Learning Multiple Layers of Features from Tiny Images
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• A Closer Look at Invalid Action Masking in Policy Gradient Algorithms (2020) — 526 citations
• CleanRL: High-quality Single-file Implementations of Deep Reinforcement Learning Algorithms (2022) — 510 citations