Guillaume Stempfel

Statistical Learning Theory · 2007–2009

A researcher in the Science corpus: 3 papers; trusts 18 researchers and is trusted by 14 researchers here, as inferred from the citation graph.

Subfields

Whom Guillaume Stempfel trusts overall

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

  1. Christopher K. I. Williams
  2. Olivier Chapelle
  3. Peter L. Bartlett
  4. John Shawe-Taylor
  5. Gunnar Rätsch
  6. Laurent Zwald
  7. Shahar Mendelson
  8. Vladimir Naumovich Vapni
  9. David A. McAllester
  10. Yuhai Wu

Who trusts Guillaume Stempfel overall

  1. Benoît Frénay
  2. Giorgio Patrini
  3. Battista Biggio
  4. Nagarajan Natarajan
  5. Zhiyi Tian
  6. Michel Verleysen
  7. Nicolas Papernot
  8. Blaine Nelson
  9. Inderjit S. Dhillon
  10. Lei Cui

Papers from Guillaume Stempfel's perspective

Ordered by how strongly the researchers Guillaume Stempfel 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. Gradient-based learning applied to document recognition
  4. The Nature of Statistical Learning Theory
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Learning Multiple Layers of Features from Tiny Images
  7. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  8. Long Short-Term Memory
  9. Attention is All you Need (Neural Information Processing Systems)
  10. ImageNet: A large-scale hierarchical image database

Their papers