Peter Prettenhofer

Artificial Intelligence · 2010–2013

A researcher in the Science corpus: 3 papers; trusts 12 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Peter Prettenhofer trusts overall

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

  1. Rie Kubota Ando
  2. John Blitzer
  3. Tong Zhang
  4. Ariadna Quattoni
  5. Shai Shalev-Shwartz
  6. Susan T. Dumais
  7. Michael Collins
  8. Fernando C Pereira
  9. Yoram Singer
  10. Bo Pang

Who trusts Peter Prettenhofer overall

  1. Hua Wang
  2. Yuhong Guo
  3. Aditya Mogadala
  4. Lixin Duan
  5. Xinjie Zhou
  6. Feiping Nie
  7. Heng Huang
  8. Xiaojun Wan
  9. Lili Mou
  10. Min Xiao

Papers from Peter Prettenhofer's perspective

Ordered by how strongly the researchers Peter Prettenhofer 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. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Long Short-Term Memory
  7. ImageNet: A large-scale hierarchical image database
  8. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  9. Going deeper with convolutions
  10. BERT: Pre-training of Deep Bidirectional Transformers for Language Understanding (North American Chapter of the Association for Computational Linguistics)

Their papers