Katie Luo

Reinforcement Learning · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 30 researchers and is trusted by 32 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 21 citations into it; #546 of 2,242 by trust here, #959 by citations
• Artificial Intelligence — 16 citations into it
• Control and Systems Engineering — 6 citations into it

Whom Katie Luo trusts overall

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

1. Sergey Levine
2. Brian D. Ziebart
3. Chelsea Finn
4. Pieter Abbeel
5. John Schulman
6. Jonathan Ho
7. Geoffrey E. Hinton
8. Andrew Y. Ng
9. Diederik P. Kingma
10. Richard S. Sutton

Who trusts Katie Luo overall

1. Sergey Levine
2. Faraz Torabi
3. Benjamin Eysenbach
4. Justin Fu
5. Kelvin Xu
6. Lisa Lee
7. Ilya Kostrikov
8. Danfei Xu
9. Garrett Warnell
10. Avi Singh

Papers from Katie Luo's perspective

Ordered by how strongly the researchers Katie Luo 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. Gradient-based learning applied to document recognition
5. Long Short-Term Memory
6. Attention is All you Need (Neural Information Processing Systems)
7. ImageNet: A large-scale hierarchical image database
8. GENERATIVE ADVERSARIAL NETS
9. Learning Multiple Layers of Features from Tiny Images
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Learning Robust Rewards with Adversarial Inverse Reinforcement Learning (2017) — 869 citations
• Learning Robust Rewards with Adverserial Inverse Reinforcement Learning (2018) — 257 citations