Nicole Beringer

2005

A researcher in the Science corpus: 1 paper; trusts 3 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Whom Nicole Beringer trusts overall

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

  1. Lawrence R. Rabiner
  2. Alex Graves
  3. J. Urgen Schmidhuber
  4. Sepp Hochreiter
  5. Susannah Young
  6. Mike Schuster
  7. Geoffrey E. Hinton
  8. J. Schmidhuber

Papers from Nicole Beringer's perspective

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

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

Their papers