Nicolas Vayatis

Statistics and Probability · with Oudre · 2006–2020

A researcher in the Science corpus: 6 papers; trusts 100 researchers and is trusted by 18 researchers here, as inferred from the citation graph.

Subfields

Whom Nicolas Vayatis trusts overall

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

  1. Jushan Bai
  2. Robert Tibshirani
  3. Pierre Perron
  4. Piotr Fryzlewicz
  5. Marc Lavielle
  6. Zaïd Harchaoui
  7. Lawrence R. Rabiner
  8. Sara A. van de Geer
  9. Stéphane Boucheron
  10. Trevor J. Hastie

Who trusts Nicolas Vayatis overall

  1. Cynthia Rudin
  2. Shivani Agarwal
  3. Yiming Ying
  4. Tie-Yan Liu
  5. Daniel Russo
  6. José Manuel Álvarez
  7. Colin Campbell
  8. Allison Chang

Papers from Nicolas Vayatis's perspective

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

  1. ImageNet classification with deep convolutional neural networks
  2. Deep Residual Learning for Image Recognition (Computer Vision and Pattern Recognition)
  3. Regression Shrinkage and Selection via the Lasso
  4. Gradient-based learning applied to document recognition
  5. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  6. Learning Multiple Layers of Features from Tiny Images
  7. Long Short-Term Memory
  8. Attention is All you Need (Neural Information Processing Systems)
  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