K. Spuhler

2018

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

Whom K. Spuhler trusts overall

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

  1. Stephen M. Smith
  2. Diederik P. Kingma
  3. Mark Jenkinson
  4. Olaf Ronneberger
  5. John G. Sled
  6. Fang Liu
  7. Jimmy Ba
  8. Xiao Han
  9. Philipp Fischer
  10. Alex P. Zijdenbos

Papers from K. Spuhler's perspective

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

  1. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. U-Net: Convolutional Networks for Biomedical Image Segmentation (International Conference on Medical Image Computing and Computer-Assisted Intervention)
  5. Gradient-based learning applied to document recognition
  6. Attention is All you Need (Neural Information Processing Systems)
  7. Learning Multiple Layers of Features from Tiny Images
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Long Short-Term Memory
  10. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)

Their papers