Wilfried Michel

Artificial Intelligence · 2019–2020

A researcher in the Science corpus: 2 papers; trusts 22 researchers and is trusted by 3 researchers here, as inferred from the citation graph.

Subfields

Whom Wilfried Michel trusts overall

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

  1. Albert Zeyer
  2. Hermann Ney
  3. Ralf Schlüter
  4. Yoshua Bengio
  5. Timothy Dozat
  6. Sepp Hochreiter
  7. Geoffrey E. Hinton
  8. Diederik P. Kingma
  9. Reinhard Kneser
  10. J. Urgen Schmidhuber

Who trusts Wilfried Michel overall

  1. Rohit Prabhavalkar
  2. Alexei Baevski
  3. Tatiana Likhomanenko

Papers from Wilfried Michel's perspective

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

  1. Long Short-Term Memory
  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. Attention is All you Need (Neural Information Processing Systems)
  5. ImageNet classification with deep convolutional neural networks
  6. Neural Machine Translation by Jointly Learning to Align and Translate (International Conference on Learning Representations)
  7. Gradient-based learning applied to document recognition
  8. Dropout: a simple way to prevent neural networks from overfitting
  9. ImageNet: A large-scale hierarchical image database
  10. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)

Their papers