Cathy Wu

Reinforcement Learning · with Bayen · 2017–2018

A researcher in the Science corpus: 3 papers; trusts 44 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 57 citations into it
• Artificial Intelligence — 48 citations into it
• Control and Systems Engineering — 48 citations into it
• Automotive Engineering — 26 citations into it
• Transportation — 26 citations into it
• Building and Construction — 16 citations into it
• Evaluation & Benchmarks — 8 citations into it
• Computational Theory and Mathematics — 7 citations into it

Whom Cathy Wu trusts overall

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

1. Richard S. Sutton
2. John Schulman
3. Sergey Levine
4. Pieter Abbeel
5. Ronald J. Williams
6. E. Todorov
7. Geoffrey E. Hinton
8. Martin Treiber
9. Sham M. Kakade
10. Yoshua Bengio

Who trusts Cathy Wu overall

1. Sven Gronauer
2. Yaqian Zhang
3. Douwe van der Wal
4. Rafael Figueiredo Prudencio
5. Alexander Pan
6. Zhi Zhang
7. Aravind Rajeswaran
8. B. R. Kiran
9. Jiachen Yang
10. Will Grathwohl

Papers from Cathy Wu's perspective

Ordered by how strongly the researchers Cathy Wu trusts endorse each paper. Same corpus, a different order for every researcher.

1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
2. ImageNet classification with deep convolutional neural networks
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. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
9. Learning Multiple Layers of Features from Tiny Images
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Variance Reduction for Policy Gradient with Action-Dependent Factorized Baselines (2018) — 173 citations
• Flow: Architecture and Benchmarking for Reinforcement Learning in Traffic Control (2017) — 223 citations
• Flow: A Modular Learning Framework for Mixed Autonomy Traffic (2017) — 230 citations