Michael Bugert

Natural Language Processing · 2017–2018

A researcher in the Science corpus: 2 papers; trusts 2 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Michael Bugert trusts overall

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

  1. Ming Tan
  2. Richard Socher
  3. David D. Lewis
  4. Sepp Hochreiter
  5. Bing Xiang
  6. Mike Schuster
  7. C. D. Santos
  8. Xavier Glorot
  9. Yoshua Bengio
  10. Jeffrey Pennington

Papers from Michael Bugert's perspective

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

  1. Long Short-Term Memory
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. ImageNet classification with deep convolutional neural networks
  4. Gradient-based learning applied to document recognition
  5. Attention is All you Need (Neural Information Processing Systems)
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. ImageNet: A large-scale hierarchical image database
  8. Sequence to Sequence Learning with Neural Networks (Neural Information Processing Systems)
  9. Learning Multiple Layers of Features from Tiny Images
  10. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)

Their papers