André Leier

Molecular Biology · 2018–2020

A researcher in the Science corpus: 3 papers; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom André Leier trusts overall

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

  1. Kuo-Chen Chou
  2. Morten Nielsen
  3. Geoffrey E. Hinton
  4. Andrew L. Maas
  5. Bjoern Peters
  6. Claus Lundegaard
  7. Karen Simonyan

Papers from André Leier's perspective

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

  1. Long Short-Term Memory
  2. Very Deep Convolutional Networks for Large-Scale Image Recognition (International Conference on Learning Representations)
  3. Rectified Linear Units Improve Restricted Boltzmann Machines
  4. Dropout: a simple way to prevent neural networks from overfitting
  5. ImageNet classification with deep convolutional neural networks
  6. Human-level control through deep reinforcement learning
  7. Distributed Representations of Words and Phrases and their Compositionality (Neural Information Processing Systems)
  8. Learning Phrase Representations using RNN Encoder–Decoder for Statistical Machine Translation
  9. Gradient-based learning applied to document recognition
  10. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)

Their papers