Catherine Mooney

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 5 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Catherine Mooney trusts

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

  1. Rob Fergus (in Computer Vision and Pattern Recognition)
  2. Matthew D. Zeiler (in Computer Vision and Pattern Recognition)
  3. Michael Gusenbauer (in Statistics and Probability)
  4. Andrew Zisserman (in Computer Vision and Pattern Recognition)
  5. Karen Simonyan (in Computer Vision and Pattern Recognition)

Papers from Catherine Mooney's perspective

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

  1. Visualizing and Understanding Convolutional Networks
  2. Deep Inside Convolutional Networks: Visualising Image Classification Models and Saliency Maps
  3. ImageNet classification with deep convolutional neural networks
  4. Mastering the game of Go with deep neural networks and tree search
  5. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  6. Axiomatic Attribution for Deep Networks
  7. Gradient-based learning applied to document recognition
  8. The mythos of model interpretability
  9. Learning Deep Features for Discriminative Localization
  10. Towards A Rigorous Science of Interpretable Machine Learning

Their papers