Yuxi Li

Artificial Intelligence · with Schuurmans · 2009–2018

A researcher in the Science corpus: 5 papers; trusts 2,104 researchers and is trusted by 6 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 852 citations into it; #13,808 of 35,345 by trust here, #25,040 by citations
• Reinforcement Learning — 558 citations into it
• Computer Vision and Pattern Recognition — 315 citations into it
• Natural Language Processing — 166 citations into it
• Management Science and Operations Research — 97 citations into it
• Control and Systems Engineering — 88 citations into it; #2,457 of 8,257 by trust here, #5,490 by citations
• Model Architectures — 73 citations into it
• Representation & Self-Supervised Learning — 70 citations into it

Whom Yuxi Li trusts overall

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

1. Alex Krizhevsky
2. Geoffrey E. Hinton
3. Yoshua Bengio
4. Ilya Sutskever
5. Diederik P. Kingma
6. Richard S. Sutton
7. Alex Graves
8. Kaiming He
9. Yann LeCun
10. David Silver

Who trusts Yuxi Li overall

1. T. T. Gomes
2. Chao Yu
3. Afshin Oroojlooyjadid
4. Tal Ben-Nun
5. Alexander V. Bernstein
6. Pablo Hernandez-Leal
7. Alessio Zappone
8. Michael Gimelfarb
9. Oshri Naparstek
10. Meixin Zhu

Papers from Yuxi Li's perspective

Ordered by how strongly the researchers Yuxi Li 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. 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

• MapReduce for Parallel Reinforcement Learning (2011) — 30 citations
• Deep Reinforcement Learning (2018) — 137 citations
• Deep Reinforcement Learning: An Overview (2017) — 1,862 citations
• Lunar Penetrating Radar onboard the Chang'e-3 mission (2014) — 165 citations
• Dual Temporal Difference Learning (2009) — 5 citations