John Edwin Laird

Artificial Intelligence · 2000–2017

A researcher in the Science corpus: 7 papers; trusts 13 researchers and is trusted by 27 researchers here, as inferred from the citation graph.

Subfields

Whom John Edwin Laird trusts overall

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

  1. Richard Granger
  2. Jonathan Gratch
  3. Richard S. Sutton
  4. John R. Anderson
  5. Daphne Koller
  6. Klaus R. Scherer
  7. Lawrence W. Barsalou
  8. Stacy C. Marsella
  9. Andrew Barto
  10. Herbert A. Simon

Who trusts John Edwin Laird overall

  1. Richard P. Cooper
  2. Pei Wang
  3. Samuel Wintermute
  4. Iuliia Kotseruba
  5. Zhengzhong Liang
  6. Ranjan Sapkota
  7. Hongxin Zhang
  8. Stefan Wender
  9. Joon Sung Park
  10. John K. Tsotsos

Papers from John Edwin Laird's perspective

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

  1. Reinforcement Learning: An Introduction
  2. Gradient-based learning applied to document recognition
  3. ImageNet classification with deep convolutional neural networks
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. An integrated theory of the mind.
  6. Long Short-Term Memory
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Attention is All you Need (Neural Information Processing Systems)
  9. Probabilistic Graphical Models: Principles and Techniques - Adaptive Computation and Machine Learning
  10. ImageNet: A large-scale hierarchical image database

Their papers