Yijie Guo

Artificial Intelligence · 2016–2023

A researcher in the Science corpus: 7 papers; trusts 462 researchers and is trusted by 146 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 134 citations into it
• Computer Vision and Pattern Recognition — 129 citations into it; #2,969 of 21,575 by trust here, #5,013 by citations
• Reinforcement Learning — 112 citations into it; #2,021 of 2,242 by trust here, #1,519 by citations
• Management Science and Operations Research — 25 citations into it
• Generative Models — 23 citations into it
• Control and Systems Engineering — 20 citations into it
• Model Architectures — 18 citations into it
• Representation & Self-Supervised Learning — 18 citations into it; #1,816 of 3,145 by trust here, #1,090 by citations

Whom Yijie Guo trusts overall

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

1. Geoffrey E. Hinton
2. Diederik P. Kingma
3. Richard S. Sutton
4. J. Urgen Schmidhuber
5. Alex Krizhevsky
6. Yoshua Bengio
7. John Schulman
8. Yann LeCun
9. Kaiming He
10. Ilya Sutskever

Who trusts Yijie Guo overall

1. Scott Fujimoto
2. Aliaksandr Siarohin
3. Shichen Liu
4. Kaixiang Lin
5. Shixiang Shane Gu
6. Olivia Wiles
7. Daochen Zha
8. Ting-Chun Wang
9. Lorenzo Steccanella
10. Anand Gopalakrishnan

Papers from Yijie Guo's perspective

Ordered by how strongly the researchers Yijie Guo 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. Attention is All you Need (Neural Information Processing Systems)
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. ImageNet: A large-scale hierarchical image database
8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. ImageNet Large Scale Visual Recognition Challenge

Their papers

• Perspective Transformer Nets: Learning Single-View 3D Object Reconstruction without 3D Supervision (2016) — 607 citations
• Unsupervised Discovery of Object Landmarks as Structural Representations (2018) — 209 citations
• Generative Adversarial Self-Imitation Learning (2018) — 61 citations
• RVT: Robotic View Transformer for 3D Object Manipulation (2023) — 299 citations
• Batch Reinforcement Learning Through Continuation Method (2021) — 16 citations
• Predictive Information Accelerates Learning in RL (2020) — 83 citations
• Self-Imitation Learning (2018) — 307 citations