Reinhold Häb-Umbach

Signal Processing · 2001–2019

A researcher in the Science corpus: 8 papers; trusts 79 researchers and is trusted by 34 researchers here, as inferred from the citation graph.

Subfields

Whom Reinhold Häb-Umbach trusts overall

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

  1. Geoffrey E. Hinton
  2. Diederik P. Kingma
  3. Yoshua Bengio
  4. Ilya Sutskever
  5. Alex Krizhevsky
  6. Jimmy Ba
  7. Oriol Vinyals
  8. Li Deng
  9. Dong Yu
  10. Alex Graves

Who trusts Reinhold Häb-Umbach overall

  1. Jinyu Li
  2. Kateřina Žmolíková
  3. Shinji Watanabe
  4. Marc Delcroix
  5. Eduardo Fonseca
  6. Zhuo Chen
  7. Carlos Eduardo Thomaz
  8. Manli Zhu
  9. Chao Yao
  10. Marco Loog

Papers from Reinhold Häb-Umbach's perspective

Ordered by how strongly the researchers Reinhold Häb-Umbach trusts endorse each paper. Same corpus, a different order for every researcher.

  1. ImageNet classification with deep convolutional neural networks
  2. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  3. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  4. Long Short-Term Memory
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Gradient-based learning applied to document recognition
  7. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  8. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  9. ImageNet: A large-scale hierarchical image database
  10. Dropout: a simple way to prevent neural networks from overfitting

Their papers