William Koch

Reinforcement Learning · 2018

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 11 citations into it
• Control and Systems Engineering — 8 citations into it
• Aerospace Engineering — 5 citations into it

Whom William Koch trusts overall

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

1. John Schulman
2. Nathan P. Koenig
3. Douglas J. Leith
4. Jemin Hwangbo
5. Richard S. Sutton
6. Timothy P. Lillicrap
7. Pieter Abbeel
8. Greg Brockman
9. Sergey Levine
10. Andrew Y. Ng

Papers from William Koch's perspective

Ordered by how strongly the researchers William Koch 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. Reinforcement Learning: An Introduction
5. Long Short-Term Memory
6. Gradient-based learning applied to document recognition
7. Attention is All you Need (Neural Information Processing Systems)
8. Trust Region Policy Optimization (International Conference on Machine Learning)
9. ImageNet: A large-scale hierarchical image database
10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers

• Reinforcement Learning for UAV Attitude Control (2018) — 473 citations