R. Li

Artificial Intelligence · with Agrawal · 2019

A researcher in the Science corpus: 1 paper; trusts 35 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 37 citations into it
• Reinforcement Learning — 35 citations into it
• Control and Systems Engineering — 16 citations into it
• Computer Vision and Pattern Recognition — 9 citations into it

Whom R. Li trusts overall

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

1. J. Urgen Schmidhuber
2. Richard S. Sutton
3. Geoffrey E. Hinton
4. Sergey Levine
5. Yoshua Bengio
6. Diederik P. Kingma
7. Pieter Abbeel
8. Alex Krizhevsky
9. John Schulman
10. Ilya Sutskever

Who trusts R. Li overall

1. Danny Driess
2. Jung-Su Ha

Papers from R. Li's perspective

Ordered by how strongly the researchers R. 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. Learning Multiple Layers of Features from Tiny Images
9. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Towards Practical Multi-Object Manipulation using Relational Reinforcement Learning (2019) — 124 citations