Felix Schmitt

Reinforcement Learning · 2016–2021

A researcher in the Science corpus: 2 papers; trusts 8 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Reinforcement Learning — 28 citations into it
• Artificial Intelligence — 22 citations into it
• Control and Systems Engineering — 9 citations into it

Whom Felix Schmitt trusts overall

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

1. Brian D. Ziebart
2. Richard S. Sutton
3. Andrew Y. Ng

Papers from Felix Schmitt's perspective

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

1. Reinforcement Learning: An Introduction
2. Apprenticeship learning via inverse reinforcement learning
3. Maximum Entropy Inverse Reinforcement Learning
4. Algorithms for Inverse Reinforcement Learning
5. Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping
6. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
7. ImageNet classification with deep convolutional neural networks
8. Gradient-based learning applied to document recognition
9. Maximum margin planning
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Reward (Mis)design for Autonomous Driving (2021) — 169 citations
• Inverse Reinforcement Learning with Simultaneous Estimation of Rewards and Dynamics (2016) — 79 citations