Matthew Cook

Electrical and Electronic Engineering · with Diehl · 2015

A researcher in the Science corpus: 2 papers; trusts 38 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

Whom Matthew Cook trusts overall

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

  1. Daniel Neil
  2. David E. Rumelhart
  3. Yann LeCun
  4. Geoffrey E. Hinton
  5. Paul A. Merolla
  6. Shih-Chii Liu
  7. Wei Zhang
  8. Yoshua Bengio
  9. Joseph M. Brader
  10. Giacomo Indiveri

Who trusts Matthew Cook overall

  1. Kaushik Roy
  2. Bing Han
  3. S. R. Kheradpisheh
  4. Junhaeng Lee
  5. Friedemann Zenke
  6. Yujie Wu
  7. Seijoon Kim
  8. Gopalakrishnan Srinivasan
  9. Chankyu Lee
  10. Abhronil Sengupta

Papers from Matthew Cook's perspective

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

  1. Gradient-based learning applied to document recognition
  2. ImageNet classification with deep convolutional neural networks
  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. Long Short-Term Memory
  6. Dropout: a simple way to prevent neural networks from overfitting
  7. Learning Multiple Layers of Features from Tiny Images
  8. This PDF file includes: Materials and Methods
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Going deeper with convolutions

Their papers