I. Ebert‐Uphoff

Statistics and Probability · 2000–2017

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom I. Ebert‐Uphoff trusts overall

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

  1. Clive W. J. Granger
  2. Everette S. Gardner Jr.
  3. Ankush Khandelwal
  4. Lawrence R. Rabiner
  5. Sinno Jialin Pan
  6. Marie C. McGraw
  7. James H. Faghmous
  8. Vipin Kumar

Papers from I. Ebert‐Uphoff's perspective

Ordered by how strongly the researchers I. Ebert‐Uphoff trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Delving Deep into Rectifiers: Surpassing Human-Level Performance on ImageNet Classification
  3. A Survey on Transfer Learning
  4. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Long Short-Term Memory
  7. --1 CONTENTS
  8. Gradient-based learning applied to document recognition
  9. Attention is All you Need (Neural Information Processing Systems)
  10. Deep Learning

Their papers