Jun Nakanishi

Reinforcement Learning · 2002–2013

A researcher in the Science corpus: 9 papers; trusts 20 researchers and is trusted by 128 researchers here, as inferred from the citation graph.

Subfields

Whom Jun Nakanishi trusts overall

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

  1. Stefan Schaal
  2. Auke Jan Ijspeert
  3. Jan Peters
  4. Oussama Khatib
  5. Richard S. Sutton
  6. Kenji Doya
  7. Ronald J. Williams
  8. Sethu Vijayakumar
  9. E. Todorov
  10. Hajime Kimura

Who trusts Jun Nakanishi overall

  1. Jan Peters
  2. Stefan Schaal
  3. Sergey Levine
  4. Jens Kober
  5. Peter Pastor
  6. Oliver Kroemer
  7. Gerhard Neumann
  8. Christian Daniel
  9. Evangelos A. Theodorou
  10. Marc Peter Deisenroth

Papers from Jun Nakanishi's perspective

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

  1. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  2. ImageNet classification with deep convolutional neural networks
  3. Between MDPs and Semi-MDPs: A Framework for Temporal Abstraction in Reinforcement Learning
  4. Actor-Critic Algorithms
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Policy Gradient Methods for Reinforcement Learning with Function Approximation
  7. Reinforcement Learning: An Introduction
  8. Gradient-based learning applied to document recognition
  9. Long Short-Term Memory
  10. GENERATIVE ADVERSARIAL NETS

Their papers