Youngwoon Lee
Artificial Intelligence · 2012–2023
A researcher in the Science corpus: 6 papers; trusts 227 researchers and is trusted by 5 researchers here, as inferred from the citation graph.
Subfields
- Artificial Intelligence — 171 citations into it
- Reinforcement Learning — 125 citations into it; #2,217 of 2,242 by trust here, #1,999 by citations
- Computer Vision and Pattern Recognition — 110 citations into it; #15,956 of 21,575 by trust here, #13,542 by citations
- Control and Systems Engineering — 68 citations into it
- Robotics & Control — 41 citations into it
- Biomedical Engineering — 19 citations into it
- Cognitive Neuroscience — 12 citations into it
- Model Architectures — 12 citations into it
Whom Youngwoon Lee trusts overall
Their strongest outbound trust, strongest first, inferred from their citations.
- Diederik P. Kingma
- Sergey Levine
- Richard S. Sutton
- John Schulman
- Geoffrey E. Hinton
- E. Todorov
- Yoshua Bengio
- Alex Krizhevsky
- Pieter Abbeel
- Tuomas Haarnoja
Who trusts Youngwoon Lee overall
- Sven Gronauer
- Jiechuan Jiang
- Jordi Salvador
- Jingdong Wang
- Cheng Deng
- Zongqing Lu
- Klaus-Jürgen Diepold
- Taewook Nam
- Luca Weihs
- Shao-Hua Sun
Papers from Youngwoon Lee's perspective
Ordered by how strongly the researchers Youngwoon Lee trusts endorse each paper. Same corpus, a different order for every researcher.
- ImageNet classification with deep convolutional neural networks
- Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
- Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
- Attention is All you Need (Neural Information Processing Systems)
- Long Short-Term Memory
- ImageNet: A large-scale hierarchical image database
- Gradient-based learning applied to document recognition
- Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
- Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
- ImageNet Large Scale Visual Recognition Challenge
Their papers
- Spherical hashing (2012) — 466 citations
- Open X-Embodiment: Robotic Learning Datasets and RT-X Models : Open X-Embodiment Collaboration0 (2023) — 1,105 citations
- Learning to Coordinate Manipulation Skills via Skill Behavior Diversification (2020) — 100 citations
- Accelerating Reinforcement Learning with Learned Skill Priors (2020) — 317 citations
- IKEA Furniture Assembly Environment for Long-Horizon Complex Manipulation Tasks (2019) — 154 citations
- Composing Complex Skills by Learning Transition Policies (2018) — 103 citations