Pierre Alquier

Artificial Intelligence · 2007–2021

A researcher in the Science corpus: 5 papers; trusts 120 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

Whom Pierre Alquier trusts overall

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

  1. David A. McAllester
  2. Olivier Catoni
  3. Tong Zhang
  4. Gintare Karolina Dziugaite
  5. Pascal Germain
  6. Geoffrey E. Hinton
  7. Yuhai Wu
  8. Gábor Lugosi
  9. Yevgeny Seldin
  10. John Shawe-Taylor

Who trusts Pierre Alquier overall

  1. Olivier Catoni
  2. Matthieu Lerasle
  3. Mikhail Khodak
  4. Giulia Denevi
  5. Nicholas Syring
  6. Roberto Imbuzeiro Oliveira
  7. Pascal Germain
  8. Kaiyi Ji
  9. Maria-Florina Balcan
  10. Carlo Ciliberto

Papers from Pierre Alquier's perspective

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

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

Their papers