Canada Kush

Artificial Intelligence · 2021

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Canada Kush trusts overall

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

  1. Zachary Chase Lipton
  2. Q. Liao
  3. Upol Ehsan
  4. Brian Y. Lim

Papers from Canada Kush's perspective

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

  1. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  2. ImageNet classification with deep convolutional neural networks
  3. Association for Computational Linguistics " Why Should I Trust You? " Explaining the Predictions of Any Classifier
  4. The mythos of model interpretability
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  8. Towards A Rigorous Science of Interpretable Machine Learning
  9. Long Short-Term Memory
  10. A Unified Approach to Interpreting Model Predictions

Their papers