Karl Kumbier

Artificial Intelligence · 2017–2019

A researcher in the Science corpus: 3 papers; trusts 17 researchers and is trusted by 11 researchers here, as inferred from the citation graph.

Subfields

Whom Karl Kumbier trusts overall

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

  1. Nicolai Meinshausen
  2. Jerome H. Friedman
  3. Robert Tibshirani
  4. Geoffrey E. Hinton
  5. Leo Breiman
  6. Cynthia Rudin
  7. Andy Liaw
  8. Matthew D. Zeiler
  9. Rajen Dinesh Shah
  10. Jian Zhou

Who trusts Karl Kumbier overall

  1. Bin Yu
  2. Chandan Singh
  3. Xiaotong Zhang
  4. Jiaqi Guan
  5. W. James Murdoch
  6. Niklas Pfister
  7. Rina Friedberg

Papers from Karl Kumbier's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  4. Gradient-based learning applied to document recognition
  5. Long Short-Term Memory
  6. Attention is All you Need (Neural Information Processing Systems)
  7. ImageNet: A large-scale hierarchical image database
  8. ImageNet Large Scale Visual Recognition Challenge
  9. Learning Multiple Layers of Features from Tiny Images
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers