Andrew Patterson

Reinforcement Learning · 2018

A researcher in the Science corpus: 2 papers; trusts 21 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Andrew Patterson trusts overall

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

  1. Richard S. Sutton
  2. Doina Precup
  3. Hamid Reza Maei
  4. Huizhen Yu
  5. Andrew Barto
  6. Leah Hackman
  7. Satinder Singh
  8. Leemon C. Baird III
  9. Geoffrey E. Hinton
  10. Longxin Lin

Who trusts Andrew Patterson overall

  1. Yi Wan

Papers from Andrew Patterson's perspective

Ordered by how strongly the researchers Andrew Patterson 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. Reinforcement Learning: An Introduction
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. Human-level control through deep reinforcement learning
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers