Yilin Wu

Reinforcement Learning · with Abbeel · 2019

A researcher in the Science corpus: 1 paper; trusts 6 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 25 citations into it
• Artificial Intelligence — 19 citations into it
• Control and Systems Engineering — 19 citations into it
• Computer Vision and Pattern Recognition — 12 citations into it
• Robotics & Control — 9 citations into it
• Aerospace Engineering — 5 citations into it

Whom Yilin Wu trusts overall

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

1. Sergey Levine
2. Pieter Abbeel
3. John Schulman
4. E. Todorov
5. Richard S. Sutton
6. Ronald J. Williams
7. Geoffrey E. Hinton
8. Alex Krizhevsky
9. Volodymyr Mnih
10. Diederik P. Kingma

Who trusts Yilin Wu overall

1. Chen Tang
2. Daniel Seita
3. Mohit Shridhar
4. Peter R. Florence
5. Xingyu Lin

Papers from Yilin Wu's perspective

Ordered by how strongly the researchers Yilin 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. GENERATIVE ADVERSARIAL NETS
9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers

• Learning to Manipulate Deformable Objects without Demonstrations (2019) — 231 citations