Matthias Loskyll

Artificial Intelligence · 2014–2018

A researcher in the Science corpus: 2 papers; trusts 4 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

• Artificial Intelligence — 21 citations into it
• Reinforcement Learning — 20 citations into it
• Control and Systems Engineering — 13 citations into it

Whom Matthias Loskyll trusts overall

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

1. Sergey Levine
2. Jan Peters

Papers from Matthias Loskyll's perspective

Ordered by how strongly the researchers Matthias Loskyll 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. Continuous control with deep reinforcement learning (International Conference on Learning Representations)
3. MuJoCo: A physics engine for model-based control
4. End-to-End Training of Deep Visuomotor Policies
5. ImageNet classification with deep convolutional neural networks
6. Policy Invariance Under Reward Transformations: Theory and Application to Reward Shaping
7. Gradient-based learning applied to document recognition
8. Relative Entropy Policy Search
9. PILCO: A Model-Based and Data-Efficient Approach to Policy Search
10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers

• Residual Reinforcement Learning for Robot Control (2018) — 624 citations
• Human-machine-interaction in the industry 4.0 era (2014) — 594 citations