Peter Reutemann

Artificial Intelligence · 2009–2016

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 43 researchers here, as inferred from the citation graph.

Subfields

Whom Peter Reutemann trusts overall

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

  1. Geoffrey E. Hinton
  2. Min-Ling Zhang

Who trusts Peter Reutemann overall

  1. Miquel Esplà-Gomis
  2. Matthias Feurer
  3. A. D. Sá
  4. Björn Schuller
  5. Jesse Read
  6. Saif M. Mohammad
  7. Frank Hutter
  8. Albert Bifet
  9. Miloš Stanojević
  10. Erik Strumbelj

Papers from Peter Reutemann's perspective

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

  1. Reducing the Dimensionality of Data with Neural
  2. ImageNet classification with deep convolutional neural networks
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Long Short-Term Memory
  5. Gradient-based learning applied to document recognition
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Learning Multiple Layers of Features from Tiny Images
  8. Attention is All you Need (Neural Information Processing Systems)
  9. A Review on Multi-Label Learning Algorithms
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers