Thomas Rothörl

Artificial Intelligence · 2016–2018

A researcher in the Science corpus: 4 papers; trusts 29 researchers and is trusted by 7 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 70 citations into it; #15,608 of 35,345 by trust here, #4,119 by citations
• Reinforcement Learning — 62 citations into it; #1,405 of 2,242 by trust here, #416 by citations
• Control and Systems Engineering — 24 citations into it; #6,280 of 8,257 by trust here, #557 by citations
• Computational Theory and Mathematics — 11 citations into it
• Robotics & Control — 9 citations into it
• Mechanical Engineering — 5 citations into it

Whom Thomas Rothörl trusts overall

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

1. Sergey Levine
2. Diederik P. Kingma
3. E. Todorov
4. Geoffrey E. Hinton
5. Yoshua Bengio
6. Volodymyr Mnih
7. Richard S. Sutton
8. J. Urgen Schmidhuber
9. Alex Krizhevsky
10. Pieter Abbeel

Who trusts Thomas Rothörl overall

1. Ignasi Clavera Gilaberte
2. Avi Singh

Papers from Thomas Rothörl's perspective

Ordered by how strongly the researchers Thomas Rothörl 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. Et al
9. Auto-Encoding Variational Bayes (International Conference on Learning Representations)
10. Learning Multiple Layers of Features from Tiny Images

Their papers

• Sim-to-Real Robot Learning from Pixels with Progressive Nets (2016) — 568 citations
• Leveraging Demonstrations for Deep Reinforcement Learning on Robotics Problems with Sparse Rewards (2017) — 764 citations
• Learning Awareness Models (2018) — 49 citations
• A Practical Approach to Insertion with Variable Socket Position Using Deep Reinforcement Learning (2018) — 118 citations