Shangding Gu

Artificial Intelligence · 2022–2024

A researcher in the Science corpus: 2 papers; trusts 37 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 122 citations into it
• Reinforcement Learning — 101 citations into it
• Control and Systems Engineering — 45 citations into it
• Management Science and Operations Research — 39 citations into it
• Computational Theory and Mathematics — 28 citations into it
• Statistics and Probability — 9 citations into it

Whom Shangding Gu trusts overall

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

1. Pieter Abbeel
2. Richard S. Sutton
3. Diederik P. Kingma
4. G. Tesauro
5. Geoffrey E. Hinton
6. Yinlam Chow
7. John Schulman
8. Andrew Barto
9. Dimitri P. Bertsekas
10. Vivek Shripad Borkar

Papers from Shangding Gu's perspective

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

Their papers

• A Review of Safe Reinforcement Learning: Methods, Theories, and Applications (2024) — 298 citations
• A Review of Safe Reinforcement Learning: Methods, Theory and Applications (2022) — 328 citations