Ophélie Lacroix

Artificial Intelligence · 2016–2017

A researcher in the Science corpus: 2 papers; trusts 18 researchers and is trusted by 0 researchers here, as inferred from the citation graph.

Subfields

Whom Ophélie Lacroix trusts overall

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

  1. R. Caruana
  2. Alex Graves
  3. J. Urgen Schmidhuber
  4. Sepp Hochreiter
  5. Ronan Collobert
  6. Barbara Plank
  7. Lynn Carlson
  8. Milan Straka
  9. Geoffrey E. Hinton
  10. Yoshua Bengio

Papers from Ophélie Lacroix's perspective

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

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

Their papers