Thomas Rückstieß

Reinforcement Learning · 2008–2010

A researcher in the Science corpus: 5 papers; trusts 18 researchers and is trusted by 25 researchers here, as inferred from the citation graph.

Subfields

Whom Thomas Rückstieß trusts overall

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

  1. Jan Peters
  2. Ronald J. Williams
  3. Stefan Schaal
  4. Richard S. Sutton
  5. Daan Wierstra
  6. Jonathan Baxter
  7. J. Urgen Schmidhuber
  8. Yi Sun
  9. Tom Schaul
  10. Christopher J. C. H. Watkins

Who trusts Thomas Rückstieß overall

  1. J. Urgen Schmidhuber
  2. Marc Peter Deisenroth
  3. Jan Peters
  4. Gerhard Neumann
  5. Rajesh Ranganath
  6. Frank Sehnke
  7. Tom Schaul
  8. Sergey Levine
  9. Yoshua Bengio
  10. Freek Stulp

Papers from Thomas Rückstieß's perspective

Ordered by how strongly the researchers Thomas Rückstieß 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. Long Short-Term Memory
  4. Reinforcement Learning: An Introduction
  5. Gradient-based learning applied to document recognition
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Learning Multiple Layers of Features from Tiny Images
  9. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  10. GENERATIVE ADVERSARIAL NETS

Their papers