Tom Ward

Reinforcement Learning · 2016–2020

A researcher in the Science corpus: 3 papers; trusts 6 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

Whom Tom Ward trusts overall

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

  1. Richard S. Sutton
  2. Carl Boettiger
  3. Marc G. Bellemare
  4. Andrew Barto
  5. Volodymyr Mnih
  6. Matthew Johnson
  7. Geoffrey E. Hinton
  8. Michal Kempka
  9. Karol Gregor
  10. Yoshua Bengio

Who trusts Tom Ward overall

  1. Michael Crawshaw

Papers from Tom Ward's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Long Short-Term Memory
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Asynchronous Methods for Deep Reinforcement Learning
  8. Human-level control through deep reinforcement learning
  9. Reinforcement Learning: An Introduction
  10. ImageNet: A large-scale hierarchical image database

Their papers