Shengyi Jiang
Artificial Intelligence · 2021–2022
A researcher in the Science corpus: 2 papers; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 39 citations into it
- Reinforcement Learning — 36 citations into it
- Cognitive Neuroscience — 8 citations into it
- Computer Vision and Pattern Recognition — 8 citations into it
- Optimization & Training — 7 citations into it
- Electrical and Electronic Engineering — 6 citations into it
- Representation & Self-Supervised Learning — 5 citations into it
Whom Shengyi Jiang trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Pieter Abbeel
- Diederik P. Kingma
- Sergey Levine
- Geoffrey E. Hinton
- Chelsea Finn
- Richard S. Sutton
- Kaiming He
- Yoshua Bengio
- John Schulman
- Alex Krizhevsky
Papers from Shengyi Jiang's perspective
Ordered by how strongly the researchers Shengyi Jiang trusts endorse each paper. Same corpus, a different order for every researcher.
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- ImageNet classification with deep convolutional neural networks
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Long Short-Term Memory
- Attention is All you Need (Neural Information Processing Systems)
- Gradient-based learning applied to document recognition
- ImageNet: A large-scale hierarchical image database
- Learning Multiple Layers of Features from Tiny Images
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
Their papers
- Adapt to Environment Sudden Changes by Learning a Context Sensitive Policy (2022) — 45 citations
- Regret Minimization Experience Replay in Off-Policy Reinforcement Learning (2021) — 49 citations