Johanna Hansen

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 12 citations into it
• Artificial Intelligence — 11 citations into it

Whom Johanna Hansen trusts

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

1. Pieter Abbeel (in Artificial Intelligence)
2. Sergey Levine (in Artificial Intelligence)
3. John Schulman (in Reinforcement Learning)

Papers from Johanna Hansen's perspective

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

1. Trust Region Policy Optimization (International Conference on Machine Learning)
2. ImageNet classification with deep convolutional neural networks
3. Multitask Learning
4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
5. Gradient-based learning applied to document recognition
6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
7. Long Short-Term Memory
8. Attention is All you Need (Neural Information Processing Systems)
9. Reinforcement Learning with Unsupervised Auxiliary Tasks
10. Benchmarking Deep Reinforcement Learning for Continuous Control

Their papers

• Benchmark Environments for Multitask Learning in Continuous Domains (2017) — 42 citations