Romaric Audigier

Artificial Intelligence · 2020

A researcher in the Science corpus: 1 paper; trusts 7 researchers and is trusted by 2 researchers here, as inferred from the citation graph.

Subfields

Whom Romaric Audigier trusts

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

  1. Nikos Komodakis (in Computer Vision and Pattern Recognition)
  2. Yedid Hoshen (in Artificial Intelligence)
  3. Sergey Zagoruyko (in Computer Vision and Pattern Recognition)
  4. Shaoqing Ren (in Computer Vision and Pattern Recognition)
  5. Kaiming He (in Computer Vision and Pattern Recognition)
  6. X. Zhang (in Computer Vision and Pattern Recognition)
  7. Niv Cohen (in Artificial Intelligence)

Who trusts Romaric Audigier

  1. Hanqiu Deng (in Artificial Intelligence)
  2. Xingyu Li (in Artificial Intelligence)

Papers from Romaric Audigier's perspective

Ordered by how strongly the researchers Romaric Audigier 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. Wide Residual Networks
  3. ImageNet classification with deep convolutional neural networks
  4. Gradient-based learning applied to document recognition
  5. Learning Multiple Layers of Features from Tiny Images
  6. Adam: A Method for Stochastic Optimization (International Conference on Learning Representations)
  7. Attention is All you Need (Neural Information Processing Systems)
  8. Going deeper with convolutions
  9. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift (International Conference on Machine Learning)
  10. ImageNet: A large-scale hierarchical image database

Their papers