William H. Alexander

Cognitive Neuroscience · 2002–2015

A researcher in the Science corpus: 4 papers; trusts 25 researchers and is trusted by 26 researchers here, as inferred from the citation graph.

Subfields

Whom William H. Alexander trusts overall

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

  1. Andrew Barto
  2. A. Harry Klopf
  3. Matthew Botvinick
  4. Richard S. Sutton
  5. Clay B. Holroyd
  6. Olaf Sporns
  7. Peter S. Dayan
  8. Nick Yeung
  9. Michael E. Hasselmo
  10. Jan Gläscher

Who trusts William H. Alexander overall

  1. Andrea Soltoggio
  2. René Martin
  3. Naomi P. Friedman
  4. J. Krichmar
  5. Amitai Shenhav
  6. Matthew Botvinick
  7. Matthew L. Dixon
  8. Ben Tsuda
  9. Olaf Sporns
  10. Brian R. Cox

Papers from William H. Alexander's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Long Short-Term Memory
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. ImageNet classification with deep convolutional neural networks
  5. Gradient-based learning applied to document recognition
  6. Time-Derivative Models of Pavlovian Reinforcement
  7. Simple Statistical Gradient-Following Algorithms for Connectionist Reinforcement Learning
  8. The neural basis of human error processing: reinforcement learning, dopamine, and the error-related negativity. (Psychology Review)
  9. A Neural Substrate of Prediction and Reward
  10. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)

Their papers