Vitaly Levdik

Reinforcement Learning · 2017

A researcher in the Science corpus: 1 paper; trusts 14 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Vitaly Levdik trusts overall

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

  1. Richard S. Sutton
  2. Ronald J. Williams
  3. Martha White
  4. John Schulman
  5. Christopher J. C. H. Watkins
  6. E. Todorov
  7. Geoffrey E. Hinton
  8. Dimitri P. Bertsekas
  9. J. Urgen Schmidhuber
  10. Shangtong Zhang

Papers from Vitaly Levdik's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Human-level control through deep reinforcement learning
  3. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  4. ImageNet classification with deep convolutional neural networks
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Proximal Policy Optimization Algorithms (arXiv.org)
  7. MuJoCo: A physics engine for model-based control
  8. Gradient-based learning applied to document recognition
  9. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  10. The Arcade Learning Environment: An Evaluation Platform for General Agents

Their papers